阅读说明：本技术 低码率视频优化编码方法和装置、设备及存储介质 (Low-bit-rate video optimization coding method, device, equipment and storage medium ) 是由 彭海 徐言茂 于 2021-06-18 设计创作，主要内容包括：本申请涉及一种低码率视频优化编码方法和装置、设备及存储介质,其中方法包括：获取视频流数据,对视频流数据中的当前帧数据的状态进行判断；其中,当前帧数据的状态包括运动和静止；根据判断出的当前帧数据的状态,对当前帧数据进行降噪处理；将降噪处理后的当前帧数据输入至编码器进行编码。通过对当前要编码的视频流数据中的每一帧数据进行状态判断,然后根据判断出的状态进行相应的降噪处理,从而使得降噪处理时能够针对不同状态的帧数据进行不同的降噪滤波处理,从而在进行视频编码时引入对视频流数据的降噪处理,并对应不同状态的帧数据进行不同的降噪,这就有效提高了视频的编码效果,使得视频编码能够兼顾画面质量和流畅度。(The application relates to a low-bit-rate video optimization coding method, a device, equipment and a storage medium, wherein the method comprises the following steps: acquiring video stream data, and judging the state of current frame data in the video stream data; wherein, the state of the current frame data comprises motion and still; performing noise reduction processing on the current frame data according to the judged state of the current frame data; and inputting the current frame data subjected to noise reduction processing into an encoder for encoding. The state of each frame data in the current video stream data to be coded is judged, and then corresponding noise reduction processing is carried out according to the judged state, so that different noise reduction filtering processing can be carried out on the frame data in different states during the noise reduction processing, the noise reduction processing on the video stream data is introduced during the video coding, and different noise reduction is carried out on the frame data in different states, so that the coding effect of the video is effectively improved, and the picture quality and the fluency can be considered during the video coding.)

1. A method for optimizing and encoding a low bit rate video, comprising:

acquiring video stream data, and judging the state of current frame data in the video stream data;

wherein the states of the current frame data include motion and still;

according to the judged state of the current frame data, carrying out noise reduction processing on the current frame data;

and inputting the current frame data subjected to noise reduction processing into an encoder for encoding.

2. The method of claim 1, wherein the determining the status of the current frame data in the video stream data is performed by performing a complexity evaluation on the current frame data.

3. The method of claim 2, wherein the determining the status of the current frame data by evaluating the complexity of the current frame data comprises:

performing complexity evaluation on the current frame data by the encoder to obtain a complexity evaluation result;

according to the complexity evaluation result, combining a code rate control algorithm to obtain the quantization step length of the current frame data;

and determining the state of the current frame data based on the quantization step of the current frame data.

4. The method according to any one of claims 1 to 3, wherein performing noise reduction processing on the current frame data according to the determined state of the current frame data comprises:

determining corresponding noise reduction strength based on the judged state of the current frame data;

and performing noise reduction filtering processing on the current frame data by using the determined noise reduction strength.

5. The method according to claim 4, wherein determining the corresponding noise reduction strength based on the determined state of the current frame data comprises:

when the state of the current frame data is judged to be a motion state, determining the noise reduction intensity to be a first intensity;

when the state of the current frame data is judged to be a static state, determining the noise reduction intensity to be a second intensity;

wherein the first intensity is greater than the second intensity.

6. A low bit rate video optimization coding device is characterized by comprising a state judgment module, a noise reduction processing module and a coding module;

the state judgment module is configured to acquire video stream data and judge the state of current frame data in the video stream data;

wherein the states of the current frame data include motion and still;

the noise reduction processing module is configured to perform noise reduction processing on the current frame data according to the judged state of the current frame data;

and the encoding module is configured to input the current frame data subjected to noise reduction processing into an encoder for encoding.

7. The apparatus according to claim 6, wherein the state determination module is configured to obtain video stream data, and determine the state of current frame data in the video stream data by performing complexity evaluation on the current frame data.

8. The apparatus of claim 7, wherein the state determination module comprises a complexity evaluation sub-module, a quantization step calculation sub-module, and a state determination sub-module;

the complexity evaluation submodule is configured to perform complexity evaluation on the current frame data by the encoder to obtain a complexity evaluation result;

the quantization step calculation submodule is configured to obtain a quantization step of the current frame data according to the complexity evaluation result by combining a code rate control algorithm;

the state determination submodule is configured to determine the state of the current frame data based on the quantization step of the current frame data.

9. A low rate video optimized encoding device, comprising:

a processor;

a memory for storing processor-executable instructions;

wherein the processor is configured to implement the method of any one of claims 1 to 5 when executing the executable instructions.

10. A non-transitory computer readable storage medium having computer program instructions stored thereon, wherein the computer program instructions, when executed by a processor, implement the method of any of claims 1 to 5.

Technical Field

The present application relates to the field of video processing technologies, and in particular, to a low-bit-rate video optimal encoding method, apparatus, device, and storage medium.

Background

High-definition and ultra-high-definition video coding increasingly becomes the mainstream of video coding, and along with the rapid increase of internet video application, the low-bit rate and high-definition and ultra-high-definition video coding is more and more in demand. The low-bit rate high definition (narrowband high definition) and the ultra-high definition generally mean that the compression bit rate is one half or one third of the normal bit rate, and even lower.

For example, a 1080P25 hd h.264 normal bit rate is typically 8Mbps, and a low bit rate hd requires compression to 4Mbps, or even in extreme cases to 2 Mbps. At such a low compression rate, it is usually selected to discard part of the image details, so that it is easier to meet the low code rate requirement at the encoding stage. However, the adoption of the above method can easily cause the loss of too many details for the static picture, thereby reducing the fineness of the picture.

Disclosure of Invention

In view of this, the present application provides a low bit rate video optimization coding method, which can effectively improve video coding quality.

According to an aspect of the present application, there is provided a low-bit-rate video optimal encoding method, including:

acquiring video stream data, and judging the state of current frame data in the video stream data;

wherein the states of the current frame data include motion and still;

according to the judged state of the current frame data, carrying out noise reduction processing on the current frame data;

and inputting the current frame data subjected to noise reduction processing into an encoder for encoding.

In a possible implementation manner, when the state of the current frame data in the video stream data is determined, the complexity evaluation is performed on the current frame data.

In a possible implementation manner, when the determining the state of the current frame data is performed through a complexity evaluation of the current frame data, the method includes:

performing complexity evaluation on the current frame data by the encoder to obtain a complexity evaluation result;

according to the complexity evaluation result, combining a code rate control algorithm to obtain the quantization step length of the current frame data;

and determining the state of the current frame data based on the quantization step of the current frame data.

In a possible implementation manner, performing noise reduction processing on the current frame data according to the determined state of the current frame data includes:

determining corresponding noise reduction strength based on the judged state of the current frame data;

and performing noise reduction filtering processing on the current frame data by using the determined noise reduction strength.

In a possible implementation manner, when determining the corresponding noise reduction strength based on the determined state of the current frame data, the method includes:

when the state of the current frame data is judged to be a motion state, determining the noise reduction intensity to be a first intensity;

when the state of the current frame data is judged to be a static state, determining the noise reduction intensity to be a second intensity;

wherein the first intensity is greater than the second intensity.

According to another aspect of the present application, there is also provided a low bit rate video optimization coding apparatus, including a state judgment module, a noise reduction processing module and a coding module;

the state judgment module is configured to acquire video stream data and judge the state of current frame data in the video stream data;

wherein the states of the current frame data include motion and still;

the noise reduction processing module is configured to perform noise reduction processing on the current frame data according to the judged state of the current frame data;

and the encoding module is configured to input the current frame data subjected to noise reduction processing into an encoder for encoding.

In a possible implementation manner, the state determination module is configured to acquire video stream data, and perform complexity evaluation on current frame data in the video stream data when determining the state of the current frame data.

In a possible implementation manner, the state judgment module includes a complexity evaluation sub-module, a quantization step calculation sub-module and a state determination sub-module;

the complexity evaluation submodule is configured to perform complexity evaluation on the current frame data by the encoder to obtain a complexity evaluation result;

the quantization step calculation submodule is configured to obtain a quantization step of the current frame data according to the complexity evaluation result by combining a code rate control algorithm;

the state determination submodule is configured to determine the state of the current frame data based on the quantization step of the current frame data.

According to another aspect of the present application, there is also provided a low-rate video optimization encoding apparatus, including:

a processor;

a memory for storing processor-executable instructions;

wherein the processor is configured to execute the executable instructions to implement any of the methods described above.

According to another aspect of the present application, there is also provided a non-transitory computer readable storage medium having stored thereon computer program instructions which, when executed by a processor, implement the method of any of the preceding.

The state of each frame data in the current video stream data to be coded is judged, and then corresponding noise reduction processing is carried out according to the judged state, so that different noise reduction filtering processing can be carried out on the frame data in different states during the noise reduction processing, the noise reduction processing on the video stream data is introduced during the video coding, and different noise reduction is carried out on the frame data in different states, so that the coding effect of the video is effectively improved, and the picture quality and the fluency can be considered during the video coding.

Other features and aspects of the present application will become apparent from the following detailed description of exemplary embodiments, which proceeds with reference to the accompanying drawings.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate exemplary embodiments, features, and aspects of the application and, together with the description, serve to explain the principles of the application.

Fig. 1 shows a flowchart of a low-rate video optimized encoding method according to an embodiment of the present application;

FIG. 2 shows another flowchart of a low rate video optimized encoding method according to an embodiment of the present application;

fig. 3 is a block diagram illustrating a structure of a low bit rate video optimization coding apparatus according to an embodiment of the present application;

fig. 4 shows a block diagram of a low-bitrate video optimization coding device according to an embodiment of the present application.

Detailed Description

Various exemplary embodiments, features and aspects of the present application will be described in detail below with reference to the accompanying drawings. In the drawings, like reference numbers can indicate functionally identical or similar elements. While the various aspects of the embodiments are presented in drawings, the drawings are not necessarily drawn to scale unless specifically indicated.

The word "exemplary" is used exclusively herein to mean "serving as an example, embodiment, or illustration. Any embodiment described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments.

Furthermore, in the following detailed description, numerous specific details are set forth in order to provide a better understanding of the present application. It will be understood by those skilled in the art that the present application may be practiced without some of these specific details. In some instances, methods, means, elements and circuits that are well known to those skilled in the art have not been described in detail so as not to obscure the present application.

Fig. 1 shows a flowchart of a low-rate video optimized encoding method according to an embodiment of the present application. As shown in fig. 1, the method includes: step S100, acquiring video stream data, and judging the state of current frame data in the video stream data. Here, it should be explained that the state of the current frame data in the video stream data includes a motion state and a still state. The motion state means that the image corresponding to the current frame data is an animation image, and the still state means that the image corresponding to the current frame data is a still image.

After the state of the current frame data is determined, step S200 may be executed to perform noise reduction processing on the current frame data according to the determined state of the current frame data. Then, in step S300, the current frame data after the noise reduction processing is input to the encoder for encoding.

Therefore, according to the low-bit-rate video optimal coding method provided by the embodiment of the application, the state of each frame of data in the current video stream data to be coded is judged, and then the corresponding noise reduction processing is carried out according to the judged state, so that different noise reduction filtering processing can be carried out on the frame of data in different states during the noise reduction processing, the noise reduction processing on the video stream data is introduced during the video coding, and different noise reduction is carried out on the frame of data in different states, so that the coding effect of the video is effectively improved, and the picture quality and the fluency of the video coding can be considered at the same time.

In a possible implementation manner, when the state of the current frame data in the video stream data is determined, the determination may be performed by evaluating the complexity of the current frame data. That is, the judgment of the state of the current frame data in the video stream data is realized by performing complexity evaluation on the current frame data.

It should be noted that, in the low-bit-rate video optimal coding method according to the embodiment of the present application, the denoising process refers to removing high frequency components, including spatial high frequency components and temporal high frequency components, in video stream data, and retaining low frequency components. In terms of visual effect, the image details are removed, and large outlines are reserved.

Meanwhile, it should be noted that, in the low-bit-rate video optimal coding method according to the embodiment of the present application, when performing noise reduction processing on current frame data in video stream data, the noise reduction strength is adjusted according to the state of the current frame data. In a possible implementation manner, when the current frame data is in a motion state, a larger noise reduction intensity may be selected for noise reduction processing. When the current frame data is in a static state, the noise reduction processing can be performed by selecting a smaller noise reduction strength.

Here, as can be understood by those skilled in the art, the greater the noise reduction strength, the more image detail is removed, and the lower the code rate required by the encoder under the same parameters. On the contrary, the smaller the noise reduction intensity is, the more the image details are retained, and the higher the code rate required by the encoder is under the same parameters.

It should be further noted that, in the low-bit-rate video optimal coding method in the embodiment of the present application, when performing noise reduction processing on current frame data, the noise reduction filtering method adopted may be a high-quality 3D noise reduction filtering (high-quality noise 3D) method.

That is to say, in the low bit rate video optimal coding method according to the embodiment of the present application, when encoding the obtained video stream data, the state of current frame data in the video stream data is determined in real time, so that according to the determination result, for scenes with more still pictures in the video stream data, noise reduction filtering processing is performed with lower noise reduction strength, so as to retain more image details; for scenes with more dynamic pictures in video stream data, higher noise reduction strength is adopted for noise reduction filtering processing, so that an encoder does not need to adopt an excessively high quantization step length, a low code rate meeting requirements can be output, and the occurrence of mosaics is effectively avoided.

Further, according to the foregoing, when the state of the current frame data in the video stream data is determined, the determination may be performed by calculating the complexity evaluation of the current frame data. Specifically, firstly, the encoder performs complexity evaluation on current frame data to obtain a complexity evaluation result. And then, according to the complexity evaluation result, combining a code rate control algorithm to obtain the quantization step length of the current frame data. And then determining the state of the current frame data based on the obtained quantization step of the current frame data.

That is to say, in the low bit rate video optimal encoding method according to the embodiment of the present application, when the state of the current frame data in the video stream data is determined, so as to determine in real time whether the current frame data in the video stream data belongs to a scene with more dynamic pictures or a scene with more static pictures, the complexity of the current frame data is directly evaluated by the encoder that is currently encoding the video stream data, so that a complexity evaluation algorithm does not need to be separately designed, and a pre-analysis algorithm in the encoder is directly called to perform complexity evaluation calculation, which effectively reduces a video data processing difficulty coefficient. Meanwhile, due to the fact that the pre-analysis algorithm in the encoder is directly called when the complexity evaluation of the current frame data is calculated, the noise reduction processing and the encoding processing of the video stream data are based on the same encoder, the encoding effect of the video data is effectively improved, and high-quality video encoding is guaranteed.

Here, it should be further noted that, after the complexity evaluation of the current frame data is directly performed by using the encoder, the quantization step size of the current frame data needs to be obtained by combining the code rate control algorithm according to the complexity evaluation result of the current frame data obtained by the analysis.

In the low-bit-rate video optimal coding method, the bit rate control algorithm is also an internal inherent algorithm of the directly called encoder, so that the difficulty of processing video stream data is further simplified, and the data processing difficulty coefficient is reduced. And different code rate control algorithms are called for different encoders, so that the noise reduction processing of the current frame data in the video stream data is more matched with the encoders.

Further, in the above-described possible embodiment, when determining the state of the current frame data based on the quantization step of the current frame data, it may be implemented in the following manner.

That is, the determination is made by the magnitude relation between the quantization step of the obtained current frame data and the reference quantization step. That is, by comparing the quantization step of the current frame data with the reference quantization step, if the quantization step of the current frame data is greater than the reference quantization step, it can be determined that there are more dynamic pictures of the current frame data and the video motion degree is higher; if the quantization step size of the current frame data is smaller than the reference quantization step size, it can be determined that there are more still pictures of the current frame data and the video still degree is higher.

The value of the reference quantization step can be flexibly set according to the actual situation. Specifically, the setting may be performed according to the target code rate: the higher the target code rate is, the smaller the reference quantization step size is; the lower the target code rate, the larger the reference quantization step size is. Such as: in a possible implementation manner, the reference quantization step may be set to be: preferably, the value of the reference quantization step size is selected to be 7.

After the state of the current frame data is determined according to the above manner, the corresponding noise reduction strength can be determined based on the determined state of the current frame data, and then the determined noise reduction strength is used to perform noise reduction filtering processing on the current frame data.

When determining the corresponding noise reduction strength based on the determined state of the current frame, the method can be implemented in the following manner. Namely, when the state of the current frame data is judged to be a motion state, determining the noise reduction intensity to be a first intensity; and when the state of the current frame data is judged to be a static state, determining the noise reduction intensity to be a second intensity. Wherein the first intensity should be greater than the second intensity.

Here, it should be noted that, in the low-rate video optimal coding method according to the embodiment of the present application, the state of the current frame data may be represented by a quantization step of the current frame data. Therefore, in a possible implementation manner, when determining the noise reduction strength according to the determined state of the current frame data, the noise reduction strength during the noise reduction filtering processing of the current frame data may be determined directly according to the obtained quantization step of the current frame data.

When the noise reduction strength of the current frame data during the noise reduction filtering processing is directly determined according to the obtained quantization step size of the current frame data, the initial noise reduction strength can be calculated according to the quantization step size, and then the actual noise reduction strength of the current frame data during the noise reduction filtering processing is determined according to the calculated initial noise reduction strength.

More specifically, when the initial noise reduction strength is calculated according to the quantization step, the initial noise reduction strength can be calculated according to the formula: sdn ═ (QP-QP _ ref) × 0.2. In the calculation formula, QP _ ref is a preset reference quantization step, and a value of the reference quantization step can be determined according to a height of the target code rate.

In a possible implementation manner, according to the foregoing, the range of the reference quantization step may be set to [6, 8], and preferably, the value of the reference quantization step may be 7. QP is the quantization step size of the current frame data obtained by calculation, and Sdn is the initial noise reduction intensity obtained by calculation.

After the initial noise reduction strength is obtained through calculation, the actual noise reduction strength when the noise reduction filtering processing is performed on the current frame data can be determined according to the initial noise reduction strength. In one possible implementation manner, a range of the noise reduction strength may be defined, that is, a noise reduction strength range is defined, and then the actual noise reduction strength is determined according to a relationship between the initial noise reduction strength and the defined noise reduction strength range.

Specifically, whether the initial noise reduction strength is within the limited noise reduction strength range is judged, and if the initial noise reduction strength is within the limited noise reduction strength range, the initial noise reduction strength can be directly used as the actual noise reduction strength to perform noise reduction filtering processing on the current frame data. If the initial noise reduction intensity is larger than the upper limit value (i.e., the maximum value) in the defined noise reduction intensity range, the upper limit value in the noise reduction intensity range is directly taken as the actual noise reduction intensity. If the initial noise reduction strength is less than the lower limit (i.e., the minimum) of the defined noise reduction strength range, the lower limit in the noise reduction strength range may be directly taken as the actual noise reduction strength.

More specifically, in a possible implementation manner, the noise reduction strength range may be flexibly set according to actual situations, such as: the setting can be performed according to the target code rate. Preferably, the noise reduction intensity range may be set to [1, 9 ].

After determining the actual noise reduction intensity when performing noise reduction filtering processing on the current frame data, the determined actual noise reduction intensity can be input into a noise reduction filter, and the noise reduction filtering processing is performed on the current frame data in the video stream data.

And finally, inputting the video stream data subjected to the noise reduction filtering processing into an encoder, and carrying out video coding processing on the video stream data subjected to the noise reduction filtering processing by the encoder.

In order to more clearly illustrate the low-rate video optimal encoding method according to the embodiment of the present application, a specific embodiment of the low-rate video optimal encoding method is described in more detail below.

Referring to fig. 2, when the low-bit-rate video optimal coding method according to the embodiment of the present application is used to code the obtained video stream data, first, in step S110, frequency data is obtained, and the original current frame image data is extracted from the video stream data. Then, in step S120, complexity evaluation is performed on the current frame image data by using a pre-analysis algorithm inherent in the encoder, so as to obtain a complexity evaluation result of the current frame image data. Further, in step S130, the quantization step of the current frame image data is calculated based on the complexity evaluation result of the current frame image data obtained in the previous step by using the code rate control algorithm inherent in the encoder. Next, in step S140, the initial noise reduction intensity Sdn is calculated according to the calculated quantization step size of the current frame image data. Finally, step S150 is performed to compare the calculated initial noise reduction strength with the preset noise reduction strength range, and determine the actual noise reduction strength for performing noise reduction processing on the current frame image data. Therefore, the judgment of the state of the current frame data in the video stream data can be completed through the steps. Here, it will be understood by those skilled in the art that, in this particular embodiment, the state of the current frame data is directly characterized by the calculated quantization step size of the current frame data.

After the actual noise reduction intensity for finally performing noise reduction on the current frame data is determined, step S200 may be performed, the determined actual noise reduction intensity is used to perform noise reduction filtering processing on the current frame data, and then, in step S300, the current frame image data after the noise reduction filtering processing is input to an encoder for encoding.

Therefore, according to the low-bit-rate video optimal coding method provided by the embodiment of the application, noise reduction filtering processing is performed on each frame of data in video stream data before video coding, so that high-frequency components of pictures with high dynamic degrees, such as complex pictures, dynamic pictures and the like in the video stream data are removed, and mosaics are reduced as much as possible under a low bit rate. Meanwhile, when each frame data in the video stream data is subjected to noise reduction filtering processing, the state judgment is carried out on each frame data, so that the noise reduction filtering processing is carried out by adopting different noise reduction strengths aiming at the frame data in different states, the purpose of dynamically adjusting the noise reduction filtering strength in real time is realized, a static picture in the video stream data can keep more picture details as much as possible, a dynamic picture reduces the mosaic condition, and the video coding quality is effectively improved finally.

Correspondingly, based on any one of the low-bit-rate video optimization coding methods, the application also provides a low-bit-rate video optimization coding device. Because the working principle of the low-bit-rate video optimization coding device provided by the application is the same as or similar to that of the low-bit-rate video optimization coding method provided by the application, repeated parts are not repeated.

Referring to fig. 3, the low bit rate video optimization encoding apparatus 100 provided by the present application includes a state determination module 110, a noise reduction processing module 120, and an encoding module 130. The state determination module 110 is configured to acquire video stream data, and determine a state of current frame data in the video stream data; wherein the states of the current frame data include motion and still. And a noise reduction processing module 120 configured to perform noise reduction processing on the current frame data according to the determined state of the current frame data. And the encoding module 130 is configured to input the current frame data subjected to the noise reduction processing to an encoder for encoding.

In a possible implementation manner, the state determining module 110 is configured to acquire video stream data, and perform complexity evaluation on current frame data when determining the state of the current frame data in the video stream data.

In one possible implementation, the state determination module 110 includes a complexity evaluation sub-module, a quantization step calculation sub-module, and a state determination sub-module (not shown in the figure). And the complexity evaluation submodule is configured to perform complexity evaluation on the current frame data by the encoder to obtain a complexity evaluation result. And the quantization step calculation submodule is configured to obtain the quantization step of the current frame data by combining a code rate control algorithm according to the complexity evaluation result. And the state determining submodule is configured to determine the state of the current frame data based on the quantization step of the current frame data.

Still further, according to another aspect of the present application, there is also provided a low rate video optimized encoding apparatus 200. Referring to fig. 4, the low rate video optimization encoding apparatus 200 of the embodiment of the present application includes a processor 210 and a memory 220 for storing instructions executable by the processor 210. Wherein the processor 210 is configured to execute the executable instructions to implement any of the aforementioned low rate video optimized encoding methods.

Here, it should be noted that the number of the processors 210 may be one or more. Meanwhile, in the low-rate video optimized encoding apparatus 200 according to the embodiment of the present application, an input device 230 and an output device 240 may be further included. The processor 210, the memory 220, the input device 230, and the output device 240 may be connected via a bus, or may be connected via other methods, which is not limited in detail herein.

The memory 220, which is a computer-readable storage medium, may be used to store software programs, computer-executable programs, and various modules, such as: the program or the module corresponding to the low-bit-rate video optimization coding method in the embodiment of the application. The processor 210 executes various functional applications and data processing of the low rate video encoding apparatus 200 by executing software programs or modules stored in the memory 220.

The input device 230 may be used to receive an input number or signal. Wherein the signal may be a key signal generated in connection with user settings and function control of the device/terminal/server. The output device 240 may include a display device such as a display screen.

According to another aspect of the present application, there is also provided a non-transitory computer readable storage medium having stored thereon computer program instructions, which when executed by the processor 210, implement the low rate video optimized encoding method as described in any of the preceding.

Having described embodiments of the present application, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen in order to best explain the principles of the embodiments, the practical application, or improvements made to the technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.