阅读说明：本技术 一种数据压缩方法、数据压缩装置、电子设备 (Data compression method, data compression device and electronic equipment ) 是由 刘洋 肖灯军 曲春辉 邓云凯 杜江 马喻杰 于 2021-07-01 设计创作，主要内容包括：本申请实施例公开了一种数据压缩方法,该方法包括：基于距离向和方位向对原始回波数据中的多路并行数据进行分块,得到N个数据块；基于N个数据块中第K个数据块的标准差,对N个数据块中第K+1个数据块进行归一化处理,得到归一化后的第K+1个数据块；对归一化后的第K+1个数据块进行量化处理,得到量化后的第K+1个数据块；对量化后的第K+1个数据块进行编码,得到第K+1个数据块的编码块,并输出第K+1个数据块的编码块。本申请实施例同时还公开了一种数据压缩装置、电子设备。(The embodiment of the application discloses a data compression method, which comprises the following steps: partitioning multi-channel parallel data in original echo data based on a distance direction and an azimuth direction to obtain N data blocks; based on the standard deviation of the Kth data block in the N data blocks, carrying out normalization processing on the Kth +1 data block in the N data blocks to obtain a normalized Kth +1 data block; carrying out quantization processing on the normalized K +1 th data block to obtain a quantized K +1 th data block; and coding the quantized K +1 th data block to obtain a coding block of the K +1 th data block, and outputting the coding block of the K +1 th data block. The embodiment of the application also discloses a data compression device and electronic equipment.)

1. A method of data compression, the method comprising:

partitioning multi-channel parallel data in original echo data based on a distance direction and an azimuth direction to obtain N data blocks; wherein N is an integer greater than 2;

based on the standard deviation of the Kth data block in the N data blocks, carrying out normalization processing on the Kth +1 data block in the N data blocks to obtain a normalized Kth +1 data block; wherein K is an integer greater than or equal to 2 and less than or equal to N, and the Kth data block is a reference block of the Kth +1 data block;

quantizing the normalized K +1 th data block to obtain a quantized K +1 th data block;

and coding the quantized K +1 th data block to obtain a coding block of the K +1 th data block, and outputting the coding block of the K +1 th data block.

2. The method according to claim 1, wherein before normalizing the K +1 th data block of the N data blocks based on the standard deviation of the kth data block of the N data blocks to obtain a normalized K +1 th data block, the method further comprises:

obtaining the intra-block data module average value of the K-1 data block in the N data blocks;

determining a standard deviation of the Kth data block based on the intra-block data mean of the Kth-1 data block.

3. The method of claim 2, wherein obtaining the intra-block data block mean value of the (K-1) th data block of the N data blocks comprises

Accumulating and summing the multi-channel parallel data in the K-1 data block to obtain a first parameter;

dividing the first parameter by the number of points in the K-1 data block to obtain the intra-block data module value of the K-1 data block.

4. The method according to claim 1, wherein when K is 2, before normalizing the K +1 th data block of the N data blocks based on a standard deviation of a kth data block of the N data blocks to obtain a normalized K +1 th data block, the method includes:

acquiring the mean value of the K-1 data block in the N data blocks;

determining a standard deviation of the Kth data block based on the mean of the Kth-1 data block;

based on the standard deviation of the Kth data block, carrying out quantization processing on the Kth data block to obtain a quantized Kth data block;

and coding the quantized Kth data block to obtain a coding block of the Kth data block, and outputting the coding block of the Kth data block.

5. The method of claim 4, wherein before obtaining the mean value of the K-1 th data block of the N data blocks, the method comprises:

acquiring the mean value of the K-1 data block;

determining the standard deviation of the K-1 data block based on the mean value of the K-1 data block;

based on the standard deviation of the Kth-1 data block, carrying out quantization processing on the Kth-1 data block to obtain a quantized Kth-1 data block;

and coding the quantized K-1 data block to obtain a coding block of the K-1 data block, and outputting the coding block of the K-1 data block.

6. The method of claim 1, wherein the encoding the quantized (K + 1) th data block to obtain an encoded block of the (K + 1) th data block comprises:

receiving an encoding mode selection event;

and responding to the coding mode selection event, selecting a target coding mode, and coding the quantized K +1 th data block based on the target coding mode to obtain a coding block of the K +1 th data block.

7. The method according to claim 1, wherein the quantizing the normalized (K + 1) th data block to obtain a quantized (K + 1) th data block includes:

if the parameter value corresponding to the normalized K +1 th data block is larger than the threshold level, performing first quantization processing on the normalized K +1 th data block to obtain a quantized K +1 th data block, wherein the parameter value in the quantized K +1 th data block is first data.

8. The method of claim 7, further comprising:

and if the parameter value corresponding to the normalized K +1 th data block is smaller than the threshold level, performing second quantization processing on the normalized K +1 th data block to obtain a quantized K +1 th data block, wherein the parameter value in the quantized K +1 th data block is second data.

9. An apparatus for compressing data, the apparatus comprising:

the processing module is used for partitioning the multi-channel parallel data in the original echo data based on the distance direction and the azimuth direction to obtain N data blocks; wherein N is an integer greater than 2;

the processing module is further configured to perform normalization processing on a K +1 th data block of the N data blocks based on a standard deviation of a K-th data block of the N data blocks, so as to obtain a normalized K +1 th data block; wherein K is an integer greater than or equal to 2 and less than or equal to N, and the Kth data block is a reference block of the Kth +1 data block;

the processing module is further configured to perform quantization processing on the normalized (K + 1) th data block to obtain a quantized (K + 1) th data block;

the processing module is further configured to encode the quantized K +1 th data block to obtain an encoded block of the K +1 th data block and output the encoded block of the K +1 th data block.

10. An electronic device, characterized in that the electronic device comprises: a processor, a memory, and a communication bus;

the communication bus is used for realizing communication connection between the processor and the memory;

the memory is used for storing executable instructions;

the processor, when executing executable instructions stored in the memory, is configured to implement the data compression method of any of claims 1 to 8.

Technical Field

The present application relates to, but not limited to, the field of Synthetic Aperture Radar (SAR) signal processing, and in particular, to a data compression method, a data compression apparatus, and an electronic device.

Background

The SAR is an active microwave imaging radar with all-weather and all-day earth observation capability and has certain penetration capability to the earth surface. The two-dimensional image with high resolution is generated by actively irradiating a ground object target to obtain a backscattering echo, and the two-dimensional image is widely applied to civil and national defense fields such as flood disaster monitoring, mineral forest resource and crop general investigation, terrain mapping, military investigation, marine pollution monitoring and the like, wherein the satellite-borne synthetic aperture radar satellite is an earth observation satellite taking SAR as a payload. A transmitting device in the satellite-borne SAR system transmits radar signals to a ground interested observation area, and a receiving device in the satellite-borne SAR system receives reflected echo signals after the radar signals reach the ground. The satellite-borne SAR system generates an SAR complex image of an observation area based on the received echo signal. With the increasing demand of various fields on the resolution of the satellite-borne SAR image, the data volume and the data rate of original echo data received by a receiving device in the satellite-borne SAR system are increased sharply, but the bandwidth of a data downloading channel is limited, so that the data volume is reduced by adopting data compression in the related technology, thereby achieving the purpose of reducing the data rate. At present, a Block Adaptive Quantization (BAQ) algorithm is adopted in a satellite-borne SAR system to implement data compression. When the BAQ is adopted to compress data, the BAQ code table generated in advance is searched to obtain the BAQ compression code of the data, thereby realizing the data compression.

However, when the above method is used to compress the M-path parallel data, the occupied resources of the satellite-borne SAR system are: (D)₁+D₂+…+D_N) X M; wherein N represents the compression ratio type; d_iBAQ code table size characterizing compression ratio of i-th kind (i ═ 1, 2 … N); that is, the satellite-borne SAR system allocates a same storage resource for each path of parallel data, and is used for storing the BAQ code table of each compression ratio; obviously, along with the improvement of the resolution of the satellite-borne SAR, the data volume and the data rate of the original echo data are increased sharply, and if the original echo data are adopted continuouslyThe data compression in the mode occupies a large amount of storage resources, wastes storage space, and accordingly reduces the processing rate of the satellite-borne SAR system on the data.

Disclosure of Invention

Embodiments of the present application provide a data compression method, a data compression apparatus, an electronic device, and a computer-readable storage medium, so as to solve the problem that a data compression method in the related art occupies a large amount of storage resources and wastes storage space.

The technical scheme of the embodiment of the application is realized as follows:

the embodiment of the application provides a data compression method, which comprises the following steps:

partitioning multi-channel parallel data in original echo data based on a distance direction and an azimuth direction to obtain N data blocks; wherein N is an integer greater than 2;

based on the standard deviation of the Kth data block in the N data blocks, carrying out normalization processing on the Kth +1 data block in the N data blocks to obtain a normalized Kth +1 data block; wherein K is an integer greater than or equal to 2 and less than or equal to N, and the Kth data block is a reference block of the Kth +1 data block;

quantizing the normalized K +1 th data block to obtain a quantized K +1 th data block;

and coding the quantized K +1 th data block to obtain a coding block of the K +1 th data block and outputting the coding block of the K +1 th data block.

An apparatus for data compression, the apparatus comprising:

the processing module is used for partitioning the multi-channel parallel data in the original echo data based on the distance direction and the azimuth direction to obtain N data blocks; wherein N is an integer greater than 2;

the processing module is further configured to perform normalization processing on a K +1 th data block of the N data blocks based on a standard deviation of a K-th data block of the N data blocks, so as to obtain a normalized K +1 th data block; wherein K is an integer greater than or equal to 2 and less than or equal to N, and the Kth data block is a reference block of the Kth +1 data block;

the processing module is further configured to perform quantization processing on the normalized (K + 1) th data block to obtain a quantized (K + 1) th data block;

the processing module is further configured to encode the quantized K +1 th data block to obtain an encoded block of the K +1 th data block and output the encoded block of the K +1 th data block.

An electronic device, the electronic device comprising: a processor, a memory, and a communication bus;

the communication bus is used for realizing communication connection between the processor and the memory;

the processor, when executing the executable instructions stored in the memory, implements the steps of the data compression method described above.

A computer readable storage medium storing executable instructions for causing a processor to perform the steps of the data compression method as described above when executed.

The embodiment of the application provides a data compression method, a data compression device and electronic equipment, wherein multi-channel parallel data in original echo data are blocked based on a distance direction and an azimuth direction to obtain N data blocks; wherein N is an integer greater than 2; based on the standard deviation of the Kth data block in the N data blocks, carrying out normalization processing on the Kth +1 data block in the N data blocks to obtain a normalized Kth +1 data block; k is an integer greater than or equal to 2 and less than or equal to N, and the Kth data block is a reference block of the Kth +1 data block; carrying out quantization processing on the normalized K +1 th data block to obtain a quantized K +1 th data block; and coding the quantized K +1 th data block to obtain a coding block of the K +1 th data block and output the coding block of the K +1 th data block. Therefore, the electronic equipment for processing the K +1 th data block can directly carry out normalization processing on the K +1 th data block without acquiring the K +1 th data block, the problem of storage space waste due to the fact that the electronic equipment occupies a large amount of storage resources in the related technology is solved, occupation of storage resources of a high-speed multi-channel SAR system is reduced, the number of parallel data paths which can be processed by hardware is increased, parallel data processing speed is effectively improved, and the electronic equipment can be widely applied to the high-speed system. Meanwhile, due to the slow change of the SAR data energy, the data change of the obtained N data blocks is slow, and the coding error is reduced by independently coding the N data blocks.

Drawings

Fig. 1 is a first flowchart of a data compression method according to an embodiment of the present application;

fig. 2 is a schematic flow chart of a data compression method according to an embodiment of the present application;

fig. 3 is a schematic block diagram of processing of SAR data azimuth recursion provided in an embodiment of the present application;

fig. 4 is a schematic flow chart diagram of a data compression method according to an embodiment of the present application;

fig. 5 is a schematic structural diagram of a data compression apparatus according to an embodiment of the present application;

fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Detailed Description

The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application.

An embodiment of the present application provides a data compression method, which is applied to an electronic device, and as shown in fig. 1, the method includes:

step 101, partitioning multi-channel parallel data in original echo data based on a distance direction and an azimuth direction to obtain N data blocks.

Wherein N is an integer greater than 2.

In the embodiment of the application, the electronic device samples original echo data to obtain multiple paths of parallel data, and blocks the multiple paths of parallel data based on the distance direction and the azimuth direction to obtain N data blocks. Here, the electronic device may automatically acquire a plurality of targets in succession, forming an echo data stream with data markers.

In the embodiment of the application, a plurality of paths of parallel data, for example, 16 paths of parallel data, are partitioned according to the distance direction and the azimuth direction to obtain a data block with the size of Kr × Ka; wherein Kr corresponds to Kr sampling points in the distance direction, and Ka corresponds to Ka echo pulse numbers in the azimuth direction; the specific values of Kr and Ka can be flexibly set according to the data dynamic range of the original echo data.

In the embodiment of the application, the multi-channel parallel data acquired by the electronic equipment has the characteristic of Gaussian distribution with the buffer variance of zero mean in the distance direction and the azimuth direction.

In the embodiment of the application, the electronic equipment divides a big data block, namely, multi-channel parallel data into a plurality of small data blocks based on the distance direction and the azimuth direction, and the self-adaptive quantization of the whole data is realized by utilizing the characteristic that the dynamic range of the data in the small data blocks is far smaller than the dynamic range of the data in the whole data blocks. Globally, a greater compression of the dynamic range data is obtained.

It should be noted that one of the paths of data in the multiple paths of parallel data includes, but is not limited to, intermediate frequency signal sampling data, radio frequency signal sampling data, and quadrature data output by quadrature demodulation/filtering in the SAR system. For example, the bit width of each path of parallel data may be 32 bits, and the upper 16 bits of the 32 bits are imaginary data of the data, and the lower 16 bits are real data of the data; each way of parallel bit can also be 8 bits; the present application is not limited in any way.

In the embodiment of the application, the electronic device may store the acquired multi-channel parallel data in a Static Random-Access Memory (SRAM); the obtained multi-channel parallel data may also be stored in a Random-Access Memory (RAM), and the storage location of the multi-channel parallel data is not limited in the present application.

And 102, based on the standard deviation of the Kth data block in the N data blocks, carrying out normalization processing on the Kth +1 data block in the N data blocks to obtain a normalized Kth +1 data block.

And K is an integer greater than or equal to 2 and less than or equal to N, and the Kth data block is a reference block of the Kth +1 data block.

In the embodiment of the application, after the electronic device obtains the N data blocks obtained by the blocking of the multi-path parallel data, the electronic device sequentially performs coding processing on each data block and outputs the coded data blocks. When the electronic device determines that the kth data block in the N data blocks is an encoded data block, the K +1 th data block needs to be encoded, and the electronic device obtains a standard deviation of the kth data block.

In the embodiment of the application, after the electronic device obtains the N data blocks obtained by the blocking of the multi-path parallel data, the electronic device sequentially performs coding processing on each data block and outputs the coded data blocks. When the electronic device needs to encode the (K + 1) th data block, the electronic device obtains the standard deviation of the (K) th data block.

In the embodiment of the application, the difference exists in the multi-path parallel data in the (K + 1) th data block in the N data blocks, the data on different paths contain different evaluation indexes, different evaluation indexes can directly influence the compression effect on the (K + 1) th data block, and in order to eliminate the influence between different evaluation indexes, data standardization processing is required to solve the comparability between indexes. After data in the K +1 th data block in the N data blocks are subjected to data standardization processing, all indexes are in the same order of magnitude, and comprehensive comparison and evaluation can be performed. Wherein the data normalization process comprises a data normalization process.

In the embodiment of the present application, a processing module in an electronic device, for example, a Field Programmable Gate Array (FPGA), obtains standard deviations of K data blocks, and performs normalization processing on a K +1 th data block in N data blocks based on the standard deviation of the K data block; that is to say, the slow changing of SAR data is combined, the characteristics that the power between adjacent sub data blocks is approximately equal, the electronic device processing the K +1 th data block can directly carry out normalization processing on the K +1 th data block without acquiring the K +1 th data block, so that the real-time performance of the electronic device in normalization processing is effectively guaranteed, the occupation of FPGA storage resources is greatly reduced through the real-time calculation mode, the number of parallel data paths which can be processed by the same hardware resources is increased, and the parallel data processing rate is effectively reduced.

And 103, quantizing the normalized K +1 data block to obtain a quantized K +1 data block.

In this embodiment of the application, the quantization processing on the normalized K +1 th data block refers to a process of converting continuous multi-path parallel data in the K +1 th data block into discrete multi-path parallel data, that is, a process of approximating a continuous value in the multi-path parallel data of the K +1 th data block to a finite number of discrete values. It should be noted that, the quantization on the K +1 th normalized data block may be uniform quantization or non-uniform quantization. The quantization mode of the normalized (K + 1) th data block is not limited at all.

In the embodiment of the present application, an Analog-to-digital converter (ADC) is used to perform quantization processing on the K +1 th normalized data block.

And 104, coding the quantized K +1 th data block to obtain a coding block of the K +1 th data block, and outputting the coding block of the K +1 th data block.

In this embodiment, after acquiring the quantized K +1 th data block, a processing module in the electronic device, for example, an FPGA encodes the quantized K +1 th data block to obtain an encoded coding block, and outputs the encoded coding block to a receiving device. The coding error is reduced by independently coding the N data blocks.

The embodiment of the application provides a data compression method, which is characterized in that multi-channel parallel data in original echo data are blocked based on a distance direction and an azimuth direction to obtain N data blocks; wherein N is an integer greater than 2; based on the standard deviation of the Kth data block in the N data blocks, carrying out normalization processing on the Kth +1 data block in the N data blocks to obtain a normalized Kth +1 data block; k is an integer greater than or equal to 2 and less than or equal to N, and the Kth data block is a reference block of the Kth +1 data block; carrying out quantization processing on the normalized K +1 th data block to obtain a quantized K +1 th data block; and coding the quantized K +1 th data block to obtain a coding block of the K +1 th data block and output the coding block of the K +1 th data block. Therefore, the electronic equipment for processing the K +1 th data block can directly carry out normalization processing on the K +1 th data block without acquiring the K +1 th data block, the problem of storage space waste due to the fact that the electronic equipment occupies a large amount of storage resources in the related technology is solved, occupation of storage resources of a high-speed multi-channel SAR system is reduced, the number of parallel data paths which can be processed by hardware is increased, parallel data processing speed is effectively improved, and the electronic equipment can be widely applied to the high-speed system. Meanwhile, due to the slow change of the SAR data energy, the data change of the obtained N data blocks is slow, and the coding error is reduced by independently coding the N data blocks. .

An embodiment of the present application provides a data compression method, which is applied to an electronic device, and as shown in fig. 2, the method includes:

and step 201, partitioning the multi-channel parallel data in the original echo data based on the distance direction and the azimuth direction to obtain N data blocks.

Wherein N is an integer greater than 2.

Step 202, obtaining the intra-block data module average value of the K-1 data block in the N data blocks.

In the embodiment of the application, after the electronic equipment blocks the collected multi-path parallel data, the electronic equipment performs modular processing on each path of parallel data in the K-1 th data block to obtain a data module of each path of parallel data. For example, the 16-way parallel data in the block of the K-1 data block is subjected to modular operation to obtain 16-way parallel data modules.

And step 203, determining the standard deviation of the Kth data block based on the intra-block data module mean value of the Kth-1 data block.

In the embodiment of the application, after the electronic equipment obtains the intra-block data module average value of the K-1 data block, the standard deviation of the K data block is determined based on the intra-block data module average value of the K-1 data block. Fig. 3 is a schematic block diagram of SAR data azimuth recursive processing provided in the present application, and as shown in fig. 3, for a data block 3, a mean value of the data block 1 is obtained first, a standard deviation of the data block 2 is determined based on the obtained mean value of the data block 1, and then the data block 3 is normalized based on the standard deviation of the data block 2. The data block 1, the data block 2, the data block 3 and the data block 4 are sequentially arranged according to the flight direction of the SAR data.

Wherein, the standard deviation of the data module of the Kth block is determined by using the data module mean value of the Kth block, and the formula is as follows:

it should be noted that, the electronic device needs to create two RAM spaces for the standard deviation of 16 parallel data in each block to store the result of the sum of squares of the mean difference and the data of each block of a single pulse and the standard deviation of each block of Ka pulse. For example, each address space of the RAM3 stores the sum of the squares of the distance differences to each block of data, updated once per pulse echo signal. Each address space of the RAM4 stores the standard deviation of all the same range data in Ka echo pulses, updated every Ka echo pulse.

In this embodiment of the present application, the step 202 of obtaining the intra-block data module average value of the K-1 th data block in the N data blocks may be implemented by the following steps, including:

the method comprises the following steps of firstly, accumulating and summing multiple paths of parallel data in a K-1 data block at the same time to obtain a first parameter.

In the embodiment of the application, the electronic device accumulates the modulus of each path of parallel data in the (K-1) th data block through the accumulator array simultaneously to obtain the accumulated (K-1) th data block, namely, the first parameter. For example, 16 paths of parallel data in the K-1 th data block are simultaneously accumulated and summed to obtain the first parameter Σ A. Where A represents each way of parallel data module within the K-1 th data block.

And secondly, dividing the first parameter by the number of points in the data block of the K-1 th data block to obtain the intra-block data module average value of the data block of the K-1 th data block.

In the embodiment of the present application, the electronic device divides the first parameter by the number of points of each block to obtain a mean value u of each block data module, i.e., u ═ Σ a ÷ (kr × ka).

It should be noted that, the electronic device needs to create two Random Access Memory (RAM) spaces for simultaneously accumulating and storing 16 paths of parallel data in each block, respectively, a result of summing each block of single pulse data and an average of Ka pulse data. For example, each address space of the RAM1 stores the accumulated result for each block of data corresponding to the storage distance, and each pulse echo signal is updated once; each address space of the RAM2 stores the average of the accumulation results of the data for all the same range in Ka echo pulses, and updates every Ka echo pulse.

In this embodiment of the application, when K is 2, the electronic device encodes the K +1 th data block, that is, the 3 rd data block, and then before encoding the 3 rd data block, the electronic device encodes the K-1 th data block, that is, the 1 st data block, and the K2 nd data block, respectively.

Aiming at the Kth data block, obtaining the mean value of the Kth-1 th data block in the N data blocks; determining the standard deviation of the Kth data block based on the mean value of the Kth-1 data block; based on the standard deviation of the Kth data block, carrying out quantization processing on the Kth data block to obtain a quantized Kth data block; and coding the quantized Kth data block to obtain a coding block of the Kth data block and outputting the coding block of the Kth data block. That is to say, when the electronic device encodes the 2 nd data block, the standard deviation of the 2 nd data block is obtained based on the mean value of the 1 st data block, and the 2 nd data block is quantized based on the standard deviation of the 2 nd data block to obtain a quantized 2 nd data block; and coding the quantized 2 nd data block to obtain a coding block of the 2 nd data block and outputting the coding block of the 2 nd data block. It should be noted that, the electronic device may obtain the standard deviation of the 2 nd data block based on the mean of the 2 nd data block by averaging and calculating the standard deviation in the related art.

Aiming at the K-1 data block, obtaining the mean value of the K-1 data block; determining the standard deviation of the K-1 data block based on the mean value of the K-1 data block; based on the standard deviation of the K-1 data block, carrying out quantization processing on the K-1 data block to obtain a quantized K-1 data block; and coding the quantized K-1 data block to obtain a coding block of the K-1 data block and outputting the coding block of the K-1 data block. That is, the electronic device is based on the mean and standard deviation of the 1 st data block itself when encoding the 1 st data block.

And 204, based on the standard deviation of the Kth data block in the N data blocks, carrying out normalization processing on the Kth +1 data block in the N data blocks to obtain a normalized Kth +1 data block.

And K is an integer greater than or equal to 2 and less than or equal to N, and the Kth data block is a reference block of the Kth +1 data block.

In the embodiment of the application, the electronic device normalizes the (K + 1) th data block by performing standard deviation normalization on a module of the block data, namely dividing the module of the block data by the standard deviation to obtain a normalization result.

Step 205, if the parameter value corresponding to the normalized K +1 th data block is greater than the threshold level, performing a first quantization process on the normalized K +1 th data block to obtain a quantized K +1 th data block, where the parameter value in the quantized K +1 th data block is the first data.

And step 206, if the parameter value corresponding to the normalized (K + 1) th data block is smaller than the threshold level, performing second quantization processing on the normalized (K + 1) th data block to obtain a quantized (K + 1) th data block, wherein the parameter value in the quantized (K + 1) th data block is second data.

In the embodiment of the present application, taking the I-way data of a distance line as an example, suppose there are 32 samples I₀～I₃₁Equally divided in 4 different blocks, block 1 (I)₀～I₇) And block 3 (I)₁₆～I₂₃) Is less than a threshold level T, so that each sample is compressedThe point is only represented by a sign bit, and the coded output of 8 sampling points is 1 byte; block 2 (I)₈～I₁₅) And block 4 (I)₂₄～I₃₁) The average amplitude value of the sampling points is larger than the threshold level, 3-bit BAQ compression is adopted, namely each sampling point is represented by 3 bits, and the coded output of 8 sampling points is 3 bytes.

Step 207, receiving an encoding mode selection event.

In the embodiment of the present application, the encoding manner refers to which Bit BAQ is used for encoding N data blocks, for example, 2Bit BAQ, 3Bit BAQ, and 4Bit BAQ are used for encoding. Here, the application integrates BAQs with various compression ratios, for example, 6 types, and a person skilled in the relevant art can flexibly select a corresponding compression mode according to actual conditions, so that the flexibility of the electronic device during data processing is improved.

In the embodiment of the present application, the selection event includes a Bit of a specific code used by each of the N data blocks.

And step 208, responding to the coding mode selection event, selecting a target coding mode, and coding the quantized K +1 th data block based on the target coding mode to obtain a coding block of the K +1 th data block.

In the embodiment of the application, the electronic device receives and responds to the coding mode selection event, obtains the coding modes of the N data blocks based on the selection event, determines which Bit BAQ is specifically adopted for each data block in the N data blocks to code, and finally obtains the coding block of the (K + 1) th data block.

And step 209, outputting the coding block of the K +1 th data block.

It should be noted that, for the descriptions of the same steps and the same contents in this embodiment as those in other embodiments, reference may be made to the descriptions in other embodiments, which are not described herein again.

The embodiment of the application provides a data compression method which is applied to electronic equipment. Fig. 4 is a flowchart of another implementation of a data compression method provided in an embodiment of the present application, and as shown in fig. 4, the method includes the following steps:

step 401, inputting 16 paths of parallel data.

And step 402, partitioning the 16 paths of parallel data according to the distance direction and the azimuth direction.

And step 403, accumulating and summing the 16 data modules in each block at the same time, and dividing the sum by the number of the blocks to obtain the average value of the data modules in the block.

And step 404, calculating the standard deviation of the kth data block by using the mean value of the kth-1 data block.

Step 405, normalizing the data of the (k + 1) th block by the standard deviation of the k-th block and performing quantization comparison on the normalized data.

In step 406, the sign bit of the 16-way data and the corresponding obtained coding value form a BAQ coding compression result.

Step 407, selecting one of the compression mode results to output according to the control command.

An embodiment of the present application provides a data compression apparatus, which may be applied to a data compression method provided in the corresponding embodiments of fig. 1 to fig. 2, and as shown in fig. 5, the data compression apparatus 5 includes:

the processing module 501 is configured to block multiple paths of parallel data in original echo data based on a distance direction and an azimuth direction to obtain N data blocks; wherein N is an integer greater than 2;

the processing module 501 is further configured to perform normalization processing on a K +1 th data block of the N data blocks based on a standard deviation of the K-th data block of the N data blocks, so as to obtain a normalized K +1 th data block; k is an integer greater than or equal to 2 and less than or equal to N, and the Kth data block is a reference block of the Kth +1 data block;

the processing module 501 is further configured to perform quantization processing on the normalized K +1 th data block to obtain a quantized K +1 th data block;

the processing module 501 is further configured to encode the quantized K +1 th data block to obtain an encoding block of the K +1 th data block and output the encoding block of the K +1 th data block.

In other embodiments of the present application, the obtaining module 502 is configured to obtain an intra-block data module average value of a K-1 th data block of the N data blocks;

and the processing module 501 is configured to determine a standard deviation of the kth data block based on an intra-block data block average value of the kth-1 data block.

In other embodiments of the present application, the processing module 501 is configured to accumulate and sum multiple paths of parallel data in the K-1 th data block simultaneously to obtain a first parameter; and dividing the number of the points in the K-1 data block by the first parameter to obtain the intra-block data module average value of the K-1 data block.

In other embodiments of the present application, the obtaining module 502 is configured to obtain a mean value of a K-1 th data block of the N data blocks;

a processing module 501, configured to determine a standard deviation of a kth data block based on a mean of the kth-1 data block; based on the standard deviation of the Kth data block, carrying out quantization processing on the Kth data block to obtain a quantized Kth data block; and coding the quantized Kth data block to obtain a coding block of the Kth data block and outputting the coding block of the Kth data block.

In other embodiments of the present application, the obtaining module 502 is configured to obtain a mean value of a K-1 th data block;

a processing module 501, configured to determine a standard deviation of the K-1 th data block based on a mean of the K-1 th data block; based on the standard deviation of the K-1 data block, carrying out quantization processing on the K-1 data block to obtain a quantized K-1 data block; and coding the quantized K-1 data block to obtain a coding block of the K-1 data block and outputting the coding block of the K data block.

In other embodiments of the present application, the processing module 501 is configured to receive an encoding mode selection event; and responding to the coding mode selection event, selecting a target coding mode, and coding the quantized K +1 th data block based on the target coding mode to obtain a coding block of the K +1 th data block.

In other embodiments of the present application, the processing module 501 is configured to perform a first quantization process on the normalized K +1 th data block to obtain a quantized K +1 th data block if a parameter corresponding to the normalized K +1 th data block is greater than a threshold level, where data in the quantized K +1 th data block is first data.

In other embodiments of the present application, the processing module 501 is configured to perform a second quantization on the normalized K +1 th data block to obtain a quantized K +1 th data block if a parameter corresponding to the normalized K +1 th data block is smaller than a threshold level, where data in the quantized K +1 th data block is second data.

The embodiment of the application provides a data compression device, which is used for blocking multi-channel parallel data in original echo data based on a distance direction and an azimuth direction to obtain N data blocks; wherein N is an integer greater than 2; based on the standard deviation of the Kth data block in the N data blocks, carrying out normalization processing on the Kth +1 data block in the N data blocks to obtain a normalized Kth +1 data block; k is an integer greater than or equal to 2 and less than or equal to N, and the Kth data block is a reference block of the Kth +1 data block; carrying out quantization processing on the normalized K +1 th data block to obtain a quantized K +1 th data block; and coding the quantized K +1 th data block to obtain a coding block of the K +1 th data block and output the coding block of the K +1 th data block. Therefore, the electronic equipment for processing the K +1 th data block can directly carry out normalization processing on the K +1 th data block without acquiring the K +1 th data block, the problem of storage space waste due to the fact that the electronic equipment occupies a large amount of storage resources in the related technology is solved, occupation of storage resources of a high-speed multi-channel SAR system is reduced, the number of parallel data paths which can be processed by hardware is increased, parallel data processing speed is effectively improved, and the electronic equipment can be widely applied to the high-speed system. Meanwhile, due to the slow change of the SAR data energy, the data change of the obtained N data blocks is slow, and the coding error is reduced by independently coding the N data blocks.

It should be noted that, for a specific implementation process of the steps executed by each module in this embodiment, reference may be made to an implementation process in the data compression method provided in the embodiment corresponding to fig. 1 to fig. 2, and details are not described here again.

An embodiment of the present application provides an electronic device 6, where the electronic device 6 may be applied to an image matching method provided in the corresponding embodiments of fig. 1 to fig. 2, and as shown in fig. 6, the electronic device 6 includes: a processor 601, a memory 602, and a communication bus 603, wherein:

the communication bus 603 is used for communication between the processor 601 and the memory 602.

The processor 601 is configured to execute the data compression program stored in the memory 602 to implement a data compression method as provided in the corresponding embodiments of fig. 1 to fig. 2.

By way of example, the Processor may be an integrated circuit chip having Signal processing capabilities, such as a general purpose Processor, a Digital Signal Processor (DSP), or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or the like, wherein the general purpose Processor may be a microprocessor or any conventional Processor or the like.

Embodiments of the present application provide a computer-readable storage medium, where one or more programs are stored, and the one or more programs may be executed by one or more processors to implement an implementation process in a data compression method as provided in the embodiments corresponding to fig. 1 to fig. 2, and details of the implementation process are not repeated here.

Here, it should be noted that: the above description of the storage medium and device embodiments is similar to the description of the method embodiments above, with similar advantageous effects as the method embodiments. For technical details not disclosed in the embodiments of the storage medium and apparatus of the present application, reference is made to the description of the embodiments of the method of the present application for understanding.

The computer storage medium/Memory may be a Read Only Memory (ROM), a Programmable Read Only Memory (PROM), an Erasable Programmable Read Only Memory (EPROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), a magnetic Random Access Memory (FRAM), a Flash Memory (Flash Memory), a magnetic surface Memory, an optical Disc, or a Compact Disc Read-Only Memory (CD-ROM), and the like; but may also be various terminals such as mobile phones, computers, tablet devices, personal digital assistants, etc., that include one or any combination of the above-mentioned memories.

It should be appreciated that reference throughout this specification to "one embodiment" or "an embodiment of the present application" or "a previous embodiment" or "some embodiments" or "some implementations" means that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment of the present application. Thus, the appearances of the phrases "in one embodiment" or "in an embodiment" or "an embodiment of the present application" or "the preceding embodiments" or "some implementations" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. It should be understood that, in the various embodiments of the present application, the sequence numbers of the above-mentioned processes do not mean the execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present application. The above-mentioned serial numbers of the embodiments of the present application are merely for description and do not represent the merits of the embodiments.

In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described device embodiments are merely illustrative, for example, the division of a unit is only one logical function division, and there may be other division ways in actual implementation, such as: multiple units or components may be combined, or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the coupling, direct coupling or communication connection between the components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between the devices or units may be electrical, mechanical or other forms.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units; can be located in one place or distributed on a plurality of network units; some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, all functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may be separately regarded as one unit, or two or more units may be integrated into one unit; the integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.

The methods disclosed in the several method embodiments provided in the present application may be combined arbitrarily without conflict to obtain new method embodiments.

Features disclosed in several of the product embodiments provided in the present application may be combined in any combination to yield new product embodiments without conflict.

The features disclosed in the several method or apparatus embodiments provided in the present application may be combined arbitrarily, without conflict, to arrive at new method embodiments or apparatus embodiments.

Those of ordinary skill in the art will understand that: all or part of the steps for realizing the method embodiments can be completed by hardware related to program instructions, the program can be stored in a computer readable storage medium, and the program executes the steps comprising the method embodiments when executed; and the aforementioned storage medium includes: various media that can store program codes, such as a removable Memory device, a Read Only Memory (ROM), a magnetic disk, or an optical disk.

Alternatively, the integrated units described above in the present application may be stored in a computer-readable storage medium if they are implemented in the form of software functional modules and sold or used as independent products. Based on such understanding, the technical solutions of the embodiments of the present application may be essentially implemented or portions thereof contributing to the related art may be embodied in the form of a software product stored in a storage medium, and including several instructions for enabling a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the methods of the embodiments of the present application. And the aforementioned storage medium includes: a removable storage device, a ROM, a magnetic or optical disk, or other various media that can store program code.

It should be noted that the drawings in the embodiments of the present application are only for illustrating schematic positions of the respective devices on the terminal device, and do not represent actual positions in the terminal device, actual positions of the respective devices or the respective areas may be changed or shifted according to actual conditions (for example, a structure of the terminal device), and a scale of different parts in the terminal device in the drawings does not represent an actual scale.

The above description is only for the embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.