CN112422965A - Video code rate control method and device, computer equipment and storage medium - Google Patents
Video code rate control method and device, computer equipment and storage medium Download PDFInfo
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Abstract
The embodiment of the invention discloses a video code rate control method, a video code rate control device, computer equipment and a storage medium. The method comprises the following steps: acquiring a video I frame and information characteristics thereof; extracting the content characteristics of each coding tree unit in the video I frame by using a preset filter core; determining the actual code rate distributed to the video I frame according to the content characteristics of the current coding tree unit and the current residual code rate of the video I frame; inputting the content characteristics, the actual code rate, the current residual code rate of the current coding tree and the quantization parameters in the information characteristic collection of the video I frame into a trained learning model one by one to predict the quantization parameters of the current coding tree unit; and coding the current coding tree unit according to the quantization parameter. According to the technical scheme provided by the embodiment of the invention, the code rate is distributed by analyzing the content characteristics of the video and predicting the quantization parameters by using the learning model, so that the accuracy of code rate control is effectively improved, and the visual quality of the video is improved.
Description
Technical Field
The embodiment of the invention relates to the technical field of video coding, in particular to a video code rate control method, a video code rate control device, computer equipment and a storage medium.
Background
The bandwidth of a channel is often limited in the process of video transmission, and how to encode video by fully utilizing limited bandwidth resources and ensure good video quality is a very important issue. Therefore, rate control plays an important role in this scenario. The purpose of rate control is to reasonably use bits for coding under the condition of limited rate, so that distortion after video compression is minimum. In video coding, the types of video frames are mainly classified into I-frames, P-frames and B-frames, and rate control of I-frames is usually the most important. Because the I frame needs to be used as a reference frame for a subsequently encoded video frame to be used as a reference image, the I frame needs to consume more code rate to improve the image quality, if the I frame uses too many bits, the code rate of the subsequent video frame is lost, and on the other hand, if the I frame with low quality is used as the reference frame, the quality of the video is reduced. Therefore, balancing the code rate and distortion of I-frames is a key issue.
In the prior art, a code rate control algorithm model established by an R-lambda model is provided, and the complexity of evaluating a block by using a sum SATD is highlighted.
Disclosure of Invention
The embodiment of the invention provides a video code rate control method, a video code rate control device, computer equipment and a storage medium, so that the accuracy of code rate control is improved, and the visual quality of a video is improved.
In a first aspect, an embodiment of the present invention provides a method for controlling a video bitrate, where the method includes:
A. acquiring a video I frame and information characteristics of the video I frame, wherein the information characteristics comprise quantization parameters of the video I frame;
B. extracting content characteristics of each coding tree unit in the video I frame by using a preset filtering core, wherein the content characteristics comprise energy characteristics, intensity characteristics, shape characteristics and smoothness characteristics;
C. determining the actual code rate distributed to the current coding tree unit according to the content characteristics of the current coding tree unit and the current residual code rate of the video I frame;
D. inputting the content characteristics, the actual code rate, the current residual code rate and the quantization parameters of the video I frame of the current coding tree unit into a trained learning model to predict the quantization parameters of the current coding tree unit;
E. coding the current coding tree unit according to the quantization parameter of the current coding tree unit;
F. judging whether the current coding tree unit is the last coding tree unit in the video I frame; if yes, ending the encoding process of the video I frame; if not, updating the current coding tree unit to be the next coding tree unit and returning to execute the step C.
In a second aspect, an embodiment of the present invention further provides a device for controlling a video bitrate, where the device includes:
the information characteristic acquisition module is used for acquiring a video I frame and information characteristics of the video I frame, wherein the information characteristics comprise quantization parameters of the video I frame;
the content feature extraction module is used for extracting the content features of each coding tree unit in the video I frame by using a preset filtering core, wherein the content features comprise energy features, intensity features, shape features and smoothness features;
the actual code rate distribution module is used for determining the actual code rate distributed by the current coding tree unit according to the content characteristics of the current coding tree unit and the current residual code rate of the video I frame;
a quantization parameter prediction module, configured to input the content feature, the actual bitrate, the current residual bitrate, and a quantization parameter of the video I frame of the current coding tree unit into a trained learning model to predict a quantization parameter of the current coding tree unit;
the coding module is used for coding the current coding tree unit according to the quantization parameter of the current coding tree unit;
the ending condition judging module is used for judging whether the current coding tree unit is the last coding tree unit in the video I frame; if yes, ending the encoding process of the video I frame; if not, updating the current coding tree unit to a next coding tree unit and returning to the actual code rate allocation module for continuous execution.
In a third aspect, an embodiment of the present invention further provides a computer device, where the computer device includes:
one or more processors;
a memory for storing one or more programs;
when the one or more programs are executed by the one or more processors, the one or more processors implement the video rate control method provided by any embodiment of the invention.
In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the video rate control method provided in any embodiment of the present invention.
The embodiment of the invention provides a video code rate control method, which comprises the steps of firstly carrying out video I frame and information characteristics thereof, wherein the information characteristics comprise quantization parameters of the video I frame, then utilizing preset filtering cores to extract content characteristics such as energy characteristics, intensity characteristics, shape characteristics, smoothness characteristics and the like of each coding tree unit in the video I frame, then distributing actual code rates for the current coding tree units according to the content characteristics of the current coding tree units and the current residual code rate of the video I frame, then inputting the content characteristics, the distributed actual code rates, the current residual code rates of the current coding tree units and the quantization parameters of the video I frame into a trained learning model, predicting to obtain the quantization parameters of the current coding tree units, and finally coding the current coding tree units according to the predicted quantization parameters. According to the technical scheme provided by the embodiment of the invention, the code rate is distributed by analyzing the content characteristics of the video, and the quantitative parameters are predicted by utilizing the learning model by combining the content characteristics of the video and other characteristics of the video, so that the accuracy of code rate control is effectively improved, and the visual quality of the video is improved.
Drawings
Fig. 1 is a flowchart of a video rate control method according to an embodiment of the present invention;
FIG. 2 is a diagram illustrating the contents of a four-directional filter kernel as defined in an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a video rate control apparatus according to a second embodiment of the present invention;
fig. 4 is a schematic structural diagram of a computer device according to a third embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
Before discussing exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart may describe the steps as a sequential process, many of the steps can be performed in parallel, concurrently or simultaneously. In addition, the order of the steps may be rearranged. The process may be terminated when its operations are completed, but may have additional steps not included in the figure. The processes may correspond to methods, functions, procedures, subroutines, and the like.
Example one
Fig. 1 is a flowchart of a video rate control method according to an embodiment of the present invention. The present embodiment is applicable to the case of performing rate control on the video encoding process in video transmission, and the method may be performed by the video rate control apparatus provided in the embodiment of the present invention, and the apparatus may be implemented by hardware and/or software, and may be generally integrated in a computer device. As shown in fig. 1, the method specifically comprises the following steps:
s11, acquiring the video I frame and the information characteristics of the video I frame, wherein the information characteristics comprise the quantization parameters of the video I frame.
The I frame is also called an intra picture, and is usually the first frame of each Group of Pictures (GOP). Each frame represents a still image, in the actual video compression, various algorithms are adopted to reduce the data capacity, and the picture can be generally divided into an I frame (intra-coded frame), a P frame (forward predicted frame) and a B frame (bidirectional interpolation frame), wherein the I frame can be represented as a key frame, which can be understood as that a frame of picture is completely reserved, and the decoding can be completed only by the frame data. Specifically, in the transmission process of the video, when the input video to be coded is received, the video I frame can be obtained from the input video. While the video I-frame is acquired, the information characteristics of the video I-frame, such as Quantization Parameter (QP) used for video I-frame encoding, can also be determined by using the existing rate control algorithm.
And S12, extracting the content characteristics of each coding tree unit in the video I frame by using a preset filtering core, wherein the content characteristics comprise an energy characteristic, an intensity characteristic, a shape characteristic and a smoothness characteristic.
Specifically, when the video I-frame starts to be encoded, the content features of each coding tree unit in the video I-frame may be extracted first, so as to complete the code rate allocation by analyzing the content characteristics of the video I-frame. Specifically, each coding tree unit in the video I frame may be convolved according to a preset filter kernel to obtain a feature matrix that may represent an image contour feature, and then the content feature of each coding tree unit may be determined according to the feature matrix.
Optionally, the preset filtering kernel includes four filtering kernels with different directions, and the directions are 0 degree, 45 degrees, 90 degrees, and 135 degrees, respectively. Further optionally, extracting content features of each coding tree unit in the video I frame by using a preset filtering core, where the content features include an energy feature, an intensity feature, a shape feature, and a smoothness feature, and the method includes: performing convolution operation on the four filtering kernels and each coding tree unit in the video I frame respectively to obtain four characteristic matrixes in different directions; determining the energy characteristics according to the four characteristic matrixes and a first formula, wherein the first formula is as follows:
wherein G isf1Representing the energy characteristics, GCTU(θ, i, j) represents a gray scale value at (i, j) in the feature matrix in the θ direction, and X is [0 °,45 °,90 °,135 °]H denotes the height of the coding tree unit, W denotes the width of the coding tree unit, N denotes the number of pixels of the coding tree unit, ω1＝0.24，ω2＝0.0059，C1＝-2.4；
Determining the intensity characteristics according to the four characteristic matrixes and a second formula, wherein the second formula is as follows:
wherein G isf2Representing the intensity characteristic, ω3＝1.3；
Determining the shape characteristics according to the four characteristic matrixes and a third formula, wherein the third formula is as follows:
wherein G isf3Representing a shape feature, ω4＝0.85；
Determining the smoothness characteristic according to the four characteristic matrixes, a fourth formula and a fifth formula, wherein the fourth formula and the fifth formula are respectively as follows:
wherein G isv(theta) represents the smoothness characteristic of the coding tree unit in the theta direction, Gf4Indicating the smoothness characteristics of the coding tree unit in four directions,
representing the mean value of the characteristic matrix in the theta direction, alpha1＝2.0，α2＝1.9，ω5＝0.97，ω6＝4.2，ω7＝2.7，C2＝998。
Specifically, the content features of the image in different directions can be extracted by using four filter kernels in different directions, and then the four filter kernels are used for performing convolution operation on each coding tree unit in the video I frame, so that the contour features of the image in different angles can be obtained, and the contour features can be embodied by four feature matrixes obtained through convolution. The four filter kernels are defined as shown in fig. 2, the sizes of the four filter kernels can be 7 × 7, and the convolution operation process can be as follows:
wherein G isCTU(theta) represents a feature matrix in the theta direction obtained after the convolution operation, I represents an input code tree unit,
representing the mean value of the luminance, σ, of the input coding tree cell1When the value of θ includes 0 degree, 45 degrees, 90 degrees, and 135 degrees, four feature matrices may be obtained, and the value of each content feature of each coding tree unit is determined according to the four feature matrices. Wherein the energy characteristics can reflect the energy information of the whole coding tree unit, the intensity characteristics can reflect the intensity information of the coding tree unit in different directions, and the shape characteristics can reflect the different directions of the coding tree unitUpward shape information, smoothness feature may reflect how smooth the coding tree unit is in different directions.
And S13, determining the actual code rate allocated to the current coding tree unit according to the content characteristics of the current coding tree unit and the current residual code rate of the video I frame.
Specifically, after the content characteristics of each coding tree unit are determined, the coding process of the coding tree units may be started one by one, and the actual code rate allocated to the current coding tree unit may be determined from the first coding tree unit of the video I frame. In this embodiment, the energy characteristics in the content characteristics of the current coding tree unit may be used to measure the complexity of the current coding tree unit, and then the actual bitrate allocated to the current coding tree unit may be determined according to the energy characteristics of the current coding tree unit, the energy characteristics of the remaining coding tree units, and the current remaining bitrate of the video I frame. The current residual bit rate may be a real residual bit rate or an adjusted residual bit rate, so as to better allocate the actual bit rate.
Optionally, determining an actual bitrate allocated to the current coding tree unit according to the content characteristics of the current coding tree unit and the current remaining bitrate of the video I frame includes:
wherein the content of the first and second substances,
representing the actual bitrate of the current coding tree unit, k representing the kth coding tree unit in the video I-frame, GC (k) representing the complexity of the current coding tree unit,
representing a list of codes from a current coding treeThe sum of the complexity of the last coding tree unit of the element to video I frame, l denotes the l-th coding tree unit in video I frame, M denotes the total number of coding tree units in video I frame,
representing the current residual code rate, C3＝0.13，C4＝0.24，ω8＝4.3，α3＝1.5，α4＝2，α5＝0.5，α6＝2.02。
Optionally, the information characteristics further include an overall bit rate of the video I frame; before determining the actual code rate allocated to the current coding tree unit according to the content characteristics of the current coding tree unit and the current remaining code rate of the video I frame, the method further comprises the following steps: determining an initial code rate allocated to each coding tree unit in the video I frame according to the overall code rate and the content characteristics of each coding tree unit in the video I frame; determining the current planned residual code rate of the video I frame according to the initial code rate; determining the current actual residual code rate of the video I frame; and determining the current residual code rate according to the current planned residual code rate and the current actual residual code rate.
Specifically, the overall code rate of the video I frame may also be determined by using the existing code rate control algorithm while the video I frame is acquired. Then, an initial code rate can be pre-allocated to each coding tree unit according to the energy characteristics of each coding tree unit and the overall code rate, in the encoding process aiming at the current coding tree unit, the current planned residual code rate can be determined according to the initial code rate allocated to each residual coding tree unit, and then the current actual residual code rate is determined according to the actual code rate allocated to the coding tree unit which has completed allocation and the available overall code rate of the video I frame. The difference between the current actual residual code rate and the current planned residual code rate can represent the code rate which is more or less used than the planned code rate before the actual code rate allocated to the current coding tree unit is determined, then the current actual residual code rate can be adjusted according to the more or less used code rate, and the adjusted value is used as the current residual code rate for allocating the code rate to the current coding tree unit.
Optionally, determining an initial code rate allocated to each coding tree unit in the video I frame according to the overall code rate and the content characteristics of each coding tree unit in the video I frame includes:
wherein the content of the first and second substances,
representing the initial code rate allocated to each coding tree unit in the video I frame, k representing the kth coding tree unit in the video I frame, GC (k) representing the complexity of the current coding tree unit,
represents the sum of the complexity of all the coding tree units in the video I-frame, l represents the l-th coding tree unit in the video I-frame, M represents the total number of coding tree units in the video I-frame, RPicLevelRepresenting the overall code rate;
determining the current residual code rate according to the current planned residual code rate and the current actual residual code rate, wherein the determining comprises the following steps:
wherein the content of the first and second substances,
representing the current residual code rate, RleftRepresenting the current actual remaining code rate,
representing the sum of the initial code rates, ω, from the current coding tree unit to the last coding tree unit of the video I-frame9＝4.03，C5＝1.01。
And S14, inputting the content characteristics, the actual code rate, the current residual code rate and the quantization parameters of the video I frame of the current coding tree unit into the trained learning model to predict the quantization parameters of the current coding tree unit.
Optionally, the learning model includes a random forest algorithm model. The random forest has higher precision in a machine learning algorithm, and can overcome the defect of a single prediction model. And inputting the content characteristics, the actual code rate, the current residual code rate and the quantization parameters of the video I frame of the current coding tree unit into the trained random forest algorithm model, so as to predict the quantization parameters of the current coding tree unit.
Before prediction is performed by using the learning model, the learning model is trained and tested, and a database used for training and testing is composed of a standard test sequence of the HEVC, wherein the standard test sequence of the HEVC has 24 types, and the types can be classified into 6 types according to resolution or content characteristics. In this embodiment, 1 to 2 sequences may be selected from 6 categories, and 12 sequences in total may be used as training data, and the remaining sequences may be used as test sequences. In these video data, the coding tree units in 20 frames of images can be randomly selected from each sequence to construct a training data set and a testing data set. Then, for the coding tree units in the training data set, respectively selecting features as learning model inputs, where the features may include: the content characteristics of each coding tree unit, the code rate actually allocated by each coding tree unit, the residual code rate of the current frame corresponding to the coding process of each coding tree unit, the quantization parameter used for frame coding and the like are determined according to the method. Then, the code rate actually consumed by each coding tree unit is used as the output of the learning model, i.e. the learning model can be trained by using the training data set. And testing the learning model by using the test data set in the same mode so as to verify and adjust the model parameters. Specifically, the video coding can be divided into an open code rate control and a non-open code rate control, when the code rate control is not opened, the video is coded by using a plurality of quantization parameters, so that the quantization parameters of the frame and the coding tree unit can be obtained, and after the coding is finished, the code rates consumed by the frame and the coding tree unit can also be obtained, so that the related parameters of the training data set and the test data set can be obtained.
And S15, coding the current coding tree unit according to the quantization parameter of the current coding tree unit.
S16, judging whether the current coding tree unit is the last coding tree unit in the video I frame; if yes, ending the encoding process of the video I frame; if not, go to S17.
S17, updating the current coding tree unit to the next coding tree unit and returning to execute S13.
Specifically, in this embodiment, each time the coding process of the current coding tree unit is completed, the process of repeatedly allocating the code rate to the next coding tree unit and coding according to the predicted quantization parameter may be continued, if the current coding tree unit is the last coding tree unit in the video I frame, the coding process of the current coding tree unit is completed, that is, the coding process of the entire video I frame is completed, and at this time, a loop may be skipped to complete the coding process of the video I frame. On the basis, the whole encoding process can be repeated in the process of encoding the video I frame next time.
The technical scheme provided by the embodiment of the invention includes that firstly, a video I frame and information characteristics thereof are obtained, wherein the information characteristics comprise quantization parameters of the video I frame, then preset filtering cores are used for extracting content characteristics such as energy characteristics, strength characteristics, shape characteristics and smoothness characteristics of each coding tree unit in the video I frame, actual code rates are distributed to the current coding tree unit according to the content characteristics of the current coding tree unit and the current residual code rate of the video I frame, then the content characteristics, the distributed actual code rates, the current residual code rates and the quantization parameters of the video I frame are input into a trained learning model, the quantization parameters of the current coding tree unit are obtained through prediction, and finally the current coding tree unit is coded according to the predicted quantization parameters. By analyzing the content characteristics of the video, the code rate distribution is completed, and meanwhile, the content characteristics of the video and other characteristics of the video are combined, and the quantitative parameters are predicted by using the learning model, so that the accuracy of code rate control is effectively improved, and the visual quality of the video is improved.
Example two
Fig. 3 is a schematic structural diagram of a video bitrate control apparatus according to a second embodiment of the present invention, where the apparatus may be implemented by hardware and/or software, and may be generally integrated in a computer device. As shown in fig. 3, the apparatus includes:
an information characteristic obtaining module 31, configured to obtain a video I frame and information characteristics of the video I frame, where the information characteristics include quantization parameters of the video I frame;
the content feature extraction module 32 is configured to extract content features of each coding tree unit in the video I frame by using a preset filtering core, where the content features include an energy feature, an intensity feature, a shape feature, and a smoothness feature;
the actual code rate allocation module 33 is configured to determine, according to the content characteristics of the current coding tree unit and the current remaining code rate of the video I frame, an actual code rate allocated to the current coding tree unit;
a quantization parameter prediction module 34, configured to input the content characteristics, the actual bitrate, the current residual bitrate, and the quantization parameters of the video I frame of the current coding tree unit into the trained learning model, so as to predict the quantization parameters of the current coding tree unit;
the encoding module 35 is configured to encode the current coding tree unit according to the quantization parameter of the current coding tree unit;
an ending condition determining module 36, configured to determine whether the current coding tree unit is the last coding tree unit in the video I frame; if yes, ending the encoding process of the video I frame; if not, the current coding tree unit is updated to the next coding tree unit and returns to the actual code rate allocation module for continuous execution.
The technical scheme provided by the embodiment of the invention includes that firstly, a video I frame and information characteristics thereof are obtained, wherein the information characteristics comprise quantization parameters of the video I frame, then preset filtering cores are used for extracting content characteristics such as energy characteristics, strength characteristics, shape characteristics and smoothness characteristics of each coding tree unit in the video I frame, actual code rates are distributed to the current coding tree unit according to the content characteristics of the current coding tree unit and the current residual code rate of the video I frame, then the content characteristics, the distributed actual code rates, the current residual code rates and the quantization parameters of the video I frame are input into a trained learning model, the quantization parameters of the current coding tree unit are obtained through prediction, and finally the current coding tree unit is coded according to the predicted quantization parameters. By analyzing the content characteristics of the video, the code rate distribution is completed, and meanwhile, the content characteristics of the video and other characteristics of the video are combined, and the quantitative parameters are predicted by using the learning model, so that the accuracy of code rate control is effectively improved, and the visual quality of the video is improved.
On the basis of the above technical solution, optionally, the preset filtering kernel includes four filtering kernels with different directions, and the directions are 0 degree, 45 degrees, 90 degrees and 135 degrees, respectively.
On the basis of the above technical solution, optionally, the content feature extraction module 32 includes:
the feature matrix acquisition unit is used for performing convolution operation on the four filtering kernels and each coding tree unit in the video I frame respectively to obtain four feature matrices in different directions;
an energy characteristic determination unit, configured to determine an energy characteristic according to the four characteristic matrices and a first formula, where the first formula is:
wherein G isf1Representing the energy characteristics, GCTU(θ, i, j) represents a gray scale value at (i, j) in the feature matrix in the θ direction, and X is [0 °,45 °,90 °,135 °]H denotes the height of the coding tree unit, W denotes the width of the coding tree unit, N denotes the number of pixels of the coding tree unit, ω1＝0.24，ω2＝0.0059，C1＝-2.4；
The strength characteristic determining unit is used for determining the strength characteristic according to the four characteristic matrixes and a second formula, wherein the second formula is as follows:
wherein G isf2Representing the intensity characteristic, ω3＝1.3；
The shape feature determining unit is used for determining the shape feature according to the four feature matrixes and a third formula, wherein the third formula is as follows:
wherein G isf3Representing a shape feature, ω4＝0.85；；
The smoothness characteristic determining unit is used for determining the smoothness characteristic according to the four characteristic matrixes, a fourth formula and a fifth formula, wherein the fourth formula and the fifth formula are respectively as follows:
wherein G isv(theta) represents the smoothness characteristic of the coding tree unit in the theta direction, Gf4Indicating the smoothness characteristics of the coding tree unit in four directions,
representing the mean value of the characteristic matrix in the theta direction, alpha1＝2.0，α2＝1.9，ω5＝0.97，ω6＝4.2，ω7＝2.7，C2＝998。
On the basis of the above technical solution, optionally, the information characteristics further include an overall bit rate of the video I frame; the video rate control device further comprises:
the initial code rate determining module is used for determining the initial code rate distributed to each coding tree unit in the video I frame according to the whole code rate and the content characteristics of each coding tree unit in the video I frame before determining the actual code rate distributed to the current coding tree unit according to the content characteristics of the current coding tree unit and the current residual code rate of the video I frame;
the current plan residual code rate determining module is used for determining the current plan residual code rate of the video I frame according to the initial code rate;
the current actual residual code rate determining module is used for determining the current actual residual code rate of the video I frame;
and the current residual code rate determining module is used for determining the current residual code rate according to the current planned residual code rate and the current actual residual code rate.
On the basis of the above technical solution, optionally, the actual code rate allocation module 33 is specifically configured to:
wherein the content of the first and second substances,
representing the actual bitrate of the current coding tree unit, k representing the kth coding tree unit in the video I-frame, GC (k) representing the complexity of the current coding tree unit,
represents the sum of the complexity from the current coding tree unit to the last coding tree unit of the video I frame, l represents the ith coding tree unit in the video I frame, M represents the total number of coding tree units in the video I frame,
representing the current residual code rate, C3＝0.13，C4＝0.24，ω8＝4.3，α3＝1.5，α4＝2，α5＝0.5，α6＝2.02。
On the basis of the foregoing technical solution, optionally, the initial code rate determining module is specifically configured to:
wherein the content of the first and second substances,
representing the initial code rate allocated to each coding tree unit in the video I frame, k representing the kth coding tree unit in the video I frame, GC (k) representing the complexity of the current coding tree unit,
represents the sum of the complexity of all the coding tree units in the video I-frame, l represents the l-th coding tree unit in the video I-frame, M represents the total number of coding tree units in the video I-frame, RPicLevelRepresenting the overall code rate;
the current residual bitrate determining module is specifically configured to:
wherein the content of the first and second substances,
representing the current residual code rate, RleftRepresenting the current actual remaining code rate,
representing the sum of the initial code rates, ω, from the current coding tree unit to the last coding tree unit of the video I-frame9＝4.03，C5＝1.01。
On the basis of the above technical solution, optionally, the learning model includes a random forest algorithm model.
The video code rate control device provided by the embodiment of the invention can execute the video code rate control method provided by any embodiment of the invention, and has corresponding functional modules and beneficial effects of the execution method.
It should be noted that, in the embodiment of the video bitrate control apparatus, the included units and modules are only divided according to functional logic, but are not limited to the above division as long as the corresponding functions can be implemented; in addition, specific names of the functional units are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present invention.
EXAMPLE III
Fig. 4 is a schematic structural diagram of a computer device provided in the third embodiment of the present invention, and shows a block diagram of an exemplary computer device suitable for implementing the embodiment of the present invention. The computer device shown in fig. 4 is only an example, and should not bring any limitation to the function and the scope of use of the embodiments of the present invention. As shown in fig. 4, the computer apparatus includes a processor 41, a memory 42, an input device 43, and an output device 44; the number of the processors 41 in the computer device may be one or more, one processor 41 is taken as an example in fig. 4, the processor 41, the memory 42, the input device 43 and the output device 44 in the computer device may be connected by a bus or in other ways, and the connection by the bus is taken as an example in fig. 4.
The memory 42 is a computer-readable storage medium, and can be used for storing software programs, computer-executable programs, and modules, such as program instructions/modules corresponding to the video rate control method in the embodiment of the present invention (for example, the information feature obtaining module 31, the content feature extracting module 32, the actual rate allocating module 33, the quantization parameter predicting module 34, the encoding module 35, and the ending condition determining module 36 in the video rate control apparatus). The processor 41 executes various functional applications and data processing of the computer device by running software programs, instructions and modules stored in the memory 42, that is, implements the video rate control method described above.
The memory 42 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to use of the computer device, and the like. Further, the memory 42 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some examples, memory 42 may further include memory located remotely from processor 41, which may be connected to a computer device over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The input device 43 is operable to receive an input video I-frame and to generate key signal inputs relating to user settings and function controls of the computer apparatus, etc. The output device 44 may be used to transmit encoded video data or the like to a video receiving end.
Example four
A fourth embodiment of the present invention further provides a storage medium containing computer-executable instructions, which when executed by a computer processor, perform a video bitrate control method, the method including:
A. acquiring a video I frame and information characteristics of the video I frame, wherein the information characteristics comprise quantization parameters of the video I frame;
B. extracting content characteristics of each coding tree unit in a video I frame by using a preset filtering core, wherein the content characteristics comprise energy characteristics, intensity characteristics, shape characteristics and smoothness characteristics;
C. determining the actual code rate distributed by the current coding tree unit according to the content characteristics of the current coding tree unit and the current residual code rate of the video I frame;
D. inputting the content characteristics, the actual code rate, the current residual code rate and the quantization parameters of the video I frame of the current coding tree unit into a trained learning model so as to predict the quantization parameters of the current coding tree unit;
E. coding the current coding tree unit according to the quantization parameter of the current coding tree unit;
F. judging whether the current coding tree unit is the last coding tree unit in the video I frame; if yes, ending the encoding process of the video I frame; if not, updating the current coding tree unit to the next coding tree unit and returning to execute the step C.
The storage medium may be any of various types of memory devices or storage devices. The term "storage medium" is intended to include: mounting media such as CD-ROM, floppy disk, or tape devices; computer system memory or random access memory such as DRAM, DDR RAM, SRAM, EDO RAM, Lanbas (Rambus) RAM, etc.; non-volatile memory such as flash memory, magnetic media (e.g., hard disk or optical storage); registers or other similar types of memory elements, etc. The storage medium may also include other types of memory or combinations thereof. In addition, the storage medium may be located in the computer system in which the program is executed, or may be located in a different second computer system connected to the computer system through a network (such as the internet). The second computer system may provide the program instructions to the computer for execution. The term "storage medium" may include two or more storage media that may reside in different locations, such as in different computer systems that are connected by a network. The storage medium may store program instructions (e.g., embodied as a computer program) that are executable by one or more processors.
Of course, the storage medium containing the computer-executable instructions provided in the embodiments of the present invention is not limited to the method operations described above, and may also perform related operations in the video rate control method provided in any embodiment of the present invention.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
From the above description of the embodiments, it is obvious for those skilled in the art that the present invention can be implemented by software and necessary general hardware, and certainly, can also be implemented by hardware, but the former is a better embodiment in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as a floppy disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a FLASH Memory (FLASH), a hard disk or an optical disk of a computer, and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device) to execute the methods according to the embodiments of the present invention.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (10)
1. A method for controlling video bitrate, comprising:
A. acquiring a video I frame and information characteristics of the video I frame, wherein the information characteristics comprise quantization parameters of the video I frame;
B. extracting content characteristics of each coding tree unit in the video I frame by using a preset filtering core, wherein the content characteristics comprise energy characteristics, intensity characteristics, shape characteristics and smoothness characteristics;
C. determining the actual code rate distributed to the current coding tree unit according to the content characteristics of the current coding tree unit and the current residual code rate of the video I frame;
D. inputting the content characteristics, the actual code rate, the current residual code rate and the quantization parameters of the video I frame of the current coding tree unit into a trained learning model to predict the quantization parameters of the current coding tree unit;
E. coding the current coding tree unit according to the quantization parameter of the current coding tree unit;
F. judging whether the current coding tree unit is the last coding tree unit in the video I frame; if yes, ending the encoding process of the video I frame; if not, updating the current coding tree unit to be the next coding tree unit and returning to execute the step C.
2. The method of claim 1, wherein the predetermined filter kernels comprise four filter kernels with different directions, the directions being 0 degree, 45 degrees, 90 degrees and 135 degrees, respectively.
3. The method for controlling video bitrate according to claim 2, wherein the extracting content features of each coding tree unit in the video I-frame by using a preset filtering core, the content features including an energy feature, an intensity feature, a shape feature and a smoothness feature, comprises:
performing convolution operation on the four filtering kernels and each coding tree unit in the video I frame respectively to obtain four characteristic matrixes in different directions;
determining the energy characteristics according to the four characteristic matrixes and a first formula, wherein the first formula is as follows:
wherein G isf1Representing said energy feature, GCTU(θ, i, j) represents a gray scale value at (i, j) in the feature matrix in the θ direction, and X is [0 °,45 °,90 °,135 °]H denotes the height of the coding tree unit, W denotes the width of the coding tree unit, N denotes the number of pixels of the coding tree unit, ω1＝0.24，ω2＝0.0059，C1＝-2.4；
Determining the intensity characteristics according to the four characteristic matrixes and a second formula, wherein the second formula is as follows:
wherein G isf2Representing said intensity characteristic, ω3＝1.3；
Determining the shape feature according to the four feature matrices and a third formula, wherein the third formula is as follows:
wherein G isf3Representing said shape feature, ω4＝0.85；
Determining the smoothness characteristic according to the four characteristic matrixes, a fourth formula and a fifth formula, wherein the fourth formula and the fifth formula are respectively as follows:
wherein G isv(theta) represents the smoothness characteristic of the coding tree unit in the theta direction, Gf4Indicating the smoothness characteristics of the coding tree unit in four directions,
representing the mean value of the characteristic matrix in the theta direction, alpha1＝2.0，α2＝1.9，ω5＝0.97，ω6＝4.2，ω7＝2.7，C2＝998。
4. The video rate control method of claim 1, wherein the information characteristic further comprises an overall rate of the video I-frame;
before the determining, according to the content features of the current coding tree unit and the current remaining bitrate of the video I-frame, an actual bitrate allocated to the current coding tree unit, the method further includes:
determining an initial code rate allocated to each coding tree unit in the video I frame according to the overall code rate and the content characteristics of each coding tree unit in the video I frame;
determining the current planned residual code rate of the video I frame according to the initial code rate;
determining the current actual residual code rate of the video I frame;
and determining the current residual code rate according to the current planned residual code rate and the current actual residual code rate.
5. The method of claim 1, wherein the determining an actual bitrate allocated to the current coding tree unit according to the content characteristics of the current coding tree unit and a current remaining bitrate of the video I-frame comprises:
wherein the content of the first and second substances,
representing an actual bitrate of the current coding tree unit, k representing a kth coding tree unit in the video I-frame, GC (k) representing a complexity of the current coding tree unit,
represents a sum of complexities from the current coding tree unit to a last coding tree unit of the video I-frame,/, represents an ith coding tree unit in the video I-frame, M represents a total number of coding tree units in the video I-frame,
representing the current residual code rate, C3＝0.13，C4＝0.24，ω8＝4.3，α3＝1.5，α4＝2，α5＝0.5，α6＝2.02。
6. The method of claim 4, wherein the determining an initial bitrate allocated to each coding tree unit in the video I-frame according to the overall bitrate and the content characteristics of each coding tree unit in the video I-frame comprises:
wherein the content of the first and second substances,
is expressed as each coding tree unit in the video I frameMatching an initial code rate, k represents the kth coding tree unit in the video I frame, GC (k) represents the complexity of the current coding tree unit,
represents the sum of the complexity of all coding tree units in the video I frame, l represents the ith coding tree unit in the video I frame, M represents the total number of coding tree units in the video I frame, RPicLevelRepresenting the overall code rate;
determining the current residual bit rate according to the current planned residual bit rate and the current actual residual bit rate includes:
wherein the content of the first and second substances,
representing the current residual code rate, RleftRepresenting the current actual remaining code rate,
represents the sum of the initial code rates, ω, from the current coding tree unit to the last coding tree unit of the video I-frame9＝4.03，C5＝1.01。
7. The video rate control method of claim 1, wherein the learning model comprises a random forest algorithm model.
8. An apparatus for controlling video bitrate, comprising:
the information characteristic acquisition module is used for acquiring a video I frame and information characteristics of the video I frame, wherein the information characteristics comprise quantization parameters of the video I frame;
the content feature extraction module is used for extracting the content features of each coding tree unit in the video I frame by using a preset filtering core, wherein the content features comprise energy features, intensity features, shape features and smoothness features;
the actual code rate distribution module is used for determining the actual code rate distributed by the current coding tree unit according to the content characteristics of the current coding tree unit and the current residual code rate of the video I frame;
a quantization parameter prediction module, configured to input the content feature, the actual bitrate, the current residual bitrate, and a quantization parameter of the video I frame of the current coding tree unit into a trained learning model to predict a quantization parameter of the current coding tree unit;
the coding module is used for coding the current coding tree unit according to the quantization parameter of the current coding tree unit;
the ending condition judging module is used for judging whether the current coding tree unit is the last coding tree unit in the video I frame; if yes, ending the encoding process of the video I frame; if not, updating the current coding tree unit to a next coding tree unit and returning to the actual code rate allocation module for continuous execution.
9. A computer device, comprising:
one or more processors;
a memory for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement the video rate control method of any of claims 1-7.
10. A computer-readable storage medium, on which a computer program is stored, which, when executed by a processor, implements the video rate control method according to any of claims 1-7.
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