WO2014029315A1 - 一种获得视频编码压缩质量的方法及装置 - Google Patents

一种获得视频编码压缩质量的方法及装置 Download PDF

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Publication number
WO2014029315A1
WO2014029315A1 PCT/CN2013/081818 CN2013081818W WO2014029315A1 WO 2014029315 A1 WO2014029315 A1 WO 2014029315A1 CN 2013081818 W CN2013081818 W CN 2013081818W WO 2014029315 A1 WO2014029315 A1 WO 2014029315A1
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Prior art keywords
video
complexity
frame
code rate
rate
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PCT/CN2013/081818
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English (en)
French (fr)
Inventor
孙李娜
高山
谢清鹏
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华为技术有限公司
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Priority to EP13831434.9A priority Critical patent/EP2858364A4/en
Priority to SG11201408797RA priority patent/SG11201408797RA/en
Priority to JP2015524628A priority patent/JP5970724B2/ja
Priority to KR1020157001964A priority patent/KR101641994B1/ko
Publication of WO2014029315A1 publication Critical patent/WO2014029315A1/zh
Priority to US14/583,478 priority patent/US9906784B2/en

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Classifications

    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/134Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
    • H04N19/154Measured or subjectively estimated visual quality after decoding, e.g. measurement of distortion
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N17/00Diagnosis, testing or measuring for television systems or their details
    • H04N17/004Diagnosis, testing or measuring for television systems or their details for digital television systems
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N17/00Diagnosis, testing or measuring for television systems or their details
    • H04N17/02Diagnosis, testing or measuring for television systems or their details for colour television signals
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/102Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/134Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
    • H04N19/136Incoming video signal characteristics or properties
    • H04N19/14Coding unit complexity, e.g. amount of activity or edge presence estimation
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/134Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
    • H04N19/146Data rate or code amount at the encoder output
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/134Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
    • H04N19/157Assigned coding mode, i.e. the coding mode being predefined or preselected to be further used for selection of another element or parameter
    • H04N19/159Prediction type, e.g. intra-frame, inter-frame or bidirectional frame prediction
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/50Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using predictive coding
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/20Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
    • H04N21/23Processing of content or additional data; Elementary server operations; Server middleware
    • H04N21/234Processing of video elementary streams, e.g. splicing of video streams or manipulating encoded video stream scene graphs

Definitions

  • the present invention relates to the field of data processing technologies, and in particular, to a method and apparatus for obtaining video coding compression quality. Background technique
  • the prior art network video quality assessment method includes a full reference video quality assessment method, which uses a method of calculating a peak signal to noise ratio (PS R) to evaluate video quality.
  • the method flow generally includes: obtaining an original reference Video and terminal video; compare and calculate the original reference video and the terminal video; determine the video quality according to the specific value of the PSNR.
  • Embodiments of the present invention provide a method and apparatus for obtaining video coding compression quality, which can reduce the complexity of evaluation, and can perform video quality assessment in real time to solve the problems in the prior art.
  • an embodiment of the present invention provides a method for obtaining video coding compression quality, including: acquiring video stream information, where the video stream information includes a video frame type, a video frame size, a frame rate, and a code rate; Calculating video content complexity according to the video stream information, where the video content complexity includes time complexity or space complexity or time complexity and space complexity;
  • the video encoding compression quality is calculated based on the code rate, the frame rate, and the video content complexity.
  • the acquiring video stream information includes:
  • the code rate is determined according to a ratio of the total amount of data streams of the video stream to the predetermined time period.
  • the total data volume of the video stream is the amount of the received video stream data and the amount of the lost video stream data.
  • the calculating the video content complexity according to the video stream information includes:
  • the calculating the video content complexity according to the video stream information includes:
  • the time complexity is specifically: Among them, TCC is time complexity, BR is code rate, ABI is average I frame size, and a Q is constant.
  • the calculating the video content complexity according to the video stream information includes:
  • the calculating the video content complexity according to the video stream information includes:
  • the method further includes:
  • the corrected code rate is determined based on a ratio of the code rate to the smaller value.
  • corrected code rate is specifically:
  • the MBR is the corrected code rate
  • BR is the code rate
  • fps is the frame rate
  • 30 is the reference frame rate.
  • the calculating the video coding compression quality according to the modified code rate, the frame rate, and the video content complexity includes:
  • the video encoding compression quality is calculated based on the video encoding compression distortion and the frame rate.
  • the video coding compression distortion is specifically:
  • VDc is the video coding compression distortion
  • MOS is the video quality evaluation parameter
  • MOS max is the maximum value of the video quality evaluation parameter
  • MOS mm is the minimum value of the video quality evaluation parameter
  • MBR is the corrected code rate
  • TCC is the time complexity.
  • ai , a 2 , a 3 , a 4 are constants.
  • the calculating the video coding compression quality according to the video coding compression distortion and the frame rate comprises:
  • the difference between the maximum value of the video quality evaluation parameter and the video coding compression distortion is used as the video coding compression quality
  • the embodiment of the present invention further provides an apparatus for obtaining a video coding compression quality, including: an information acquiring unit, configured to acquire video stream information, where the video stream information includes a video frame type, a video frame size, a frame rate, and Code rate
  • a complexity calculation unit configured to calculate a video content complexity according to the video stream information acquired by the information acquiring unit, where the video content complexity includes time complexity or space complexity or time complexity and space complexity;
  • a quality evaluation unit configured to calculate a video coding compression quality according to a code rate acquired by the information acquiring unit, the frame rate, and a video content complexity obtained by the complexity calculation unit.
  • the information acquiring unit includes:
  • a code rate acquisition subunit configured to acquire a total data volume of the video stream in the predetermined time period; and determine a code rate according to a ratio of the total data volume of the video stream to the predetermined time period.
  • the complexity calculation unit includes:
  • a first time subunit configured to calculate an average I frame size in the predetermined time period according to the video frame type and size acquired by the information acquiring unit, when the video content complexity includes a time complexity; Determining the time complexity according to a ratio of the code rate to the size of the average I frame;
  • a first spatial sub-unit configured to calculate an average P frame size in the predetermined time period according to the video frame type and size acquired by the information acquiring unit, when the video content complexity includes spatial complexity;
  • the spatial complexity is determined based on a ratio of the code rate to the size of the average P frame.
  • the complexity calculation unit includes:
  • a second time subunit configured to: when the video stream information acquired by the information acquiring unit further includes a video frame quantization parameter, and the video content complexity includes a time complexity, calculate the video frame according to the video frame type Quantizing the number of bits of each pixel of the P frame under the parameter; and calculating the time complexity according to the number of bits of each pixel of the P frame and the first parameter corresponding to the quantization parameter of the video frame;
  • a second spatial subunit configured to: when the video stream information acquired by the information acquiring unit further includes a video frame quantization parameter, and the video content complexity includes a spatial complexity, calculate the video frame according to the video frame type Quantizing the number of bits of each pixel of the I frame under the parameter; and according to the number of bits of each pixel of the I frame and The second parameter corresponding to the video frame quantization parameter is used to calculate the spatial complexity.
  • a rate correcting unit configured to calculate a corrected according to the code rate and the frame rate before the quality estimating unit determines the video encoding compression quality according to the code rate, the frame rate, and the video content complexity
  • the quality evaluation unit is configured to calculate a video coding compression quality according to the modified code rate acquired by the code rate correction unit, the frame rate, and the video content complexity.
  • the code rate correction unit includes:
  • a comparison subunit configured to determine a smaller value between the frame rate and the reference frame rate acquired by the information acquiring unit
  • the quality evaluation unit includes:
  • a distortion calculation sub-unit configured to calculate a video coding compression distortion according to the corrected code rate obtained by the code rate correction unit, the video content complexity, and the video quality evaluation parameter;
  • An evaluation subunit for calculating the video coding compression quality based on the video coding compression distortion and the frame rate is an evaluation subunit for calculating the video coding compression quality based on the video coding compression distortion and the frame rate.
  • the evaluation subunit is specifically configured to use, as the video coding compression quality, a difference between a maximum value of the video quality evaluation parameter and the video coding compression distortion when the frame rate is greater than or equal to 24;
  • the difference between the maximum value of the video quality evaluation parameter and the video coding compression distortion is corrected based on the video content complexity, and the corrected result is used as the video coding compression quality.
  • the embodiment of the present invention further provides a terminal, including a first transceiver device and a first processor, where the first transceiver device is configured to receive a video stream;
  • the first processor is configured to acquire video stream information in a video stream received by the first transceiver, where the video stream information includes a video frame type, a video frame size, a frame rate, and a code rate.
  • the video stream information calculates a video content complexity, where the video content complexity includes time complexity or spatial complexity or time complexity and spatial complexity; and is calculated according to the code rate, the frame rate, and the complexity of the video content.
  • Video coding compression quality on the other hand, the embodiment of the present invention further provides a terminal, including a second transceiver device and a second processor, where the second transceiver device is configured to send a video stream;
  • the second processor is configured to acquire video stream information in a video stream sent by the second transceiver, where the video stream information includes a video frame type, a video frame size, a frame rate, and a code rate.
  • the stream information calculates the complexity of the video content, including the complexity of the time or the complexity of the space or the complexity of the time and Spatial complexity; calculating video coding compression quality according to the code rate, the frame rate, and the video content complexity.
  • the embodiment of the present invention further provides a server, where the server includes a third transceiver, and a third processor.
  • the third transceiver is configured to transmit a video stream from a sending end to a receiving end;
  • the third processor is configured to acquire video stream information in a video stream that is transmitted by the third transceiver, where the video stream information includes a video frame type, a video frame size, a frame rate, and a code rate.
  • the stream information calculates a video content complexity, the video content complexity including time complexity or space complexity or time complexity and space complexity; calculating a video according to the code rate, the frame rate, and the video content complexity Encoding compression quality.
  • the video frame information, the code rate, the frame rate, and the video content complexity of the video stream are obtained to obtain the video coding compression quality, which can be used in subsequent video quality evaluation, and the process does not need to obtain the entire
  • the original reference video and the terminal video do not need to deeply resolve the specific MV or residual value of the video stream, which greatly reduces the complexity of the video quality assessment and enables real-time evaluation.
  • the quality of the encoded compression is more in line with the subjective feelings of the human eye.
  • FIG. 1 is a flowchart of a first embodiment of a method for obtaining video coding compression quality according to the present invention
  • FIG. 2 is a flowchart of a second embodiment of a method for obtaining video coding compression quality according to the present invention
  • FIG. 4 is a flow chart of a method for obtaining time complexity in the embodiment shown in FIG. 2;
  • FIG. 5 is a flowchart of a third embodiment of a method for obtaining video coding compression quality according to the present invention
  • FIG. 6 is a flowchart of a method for obtaining spatial complexity in the embodiment shown in FIG.
  • FIG. 7 is a flowchart of a fourth embodiment of a method for obtaining video coding compression quality according to the present invention
  • FIG. 8 is a flowchart of a fifth embodiment of a method for obtaining video coding compression quality according to the present invention
  • FIG. 10 is a block diagram of a second embodiment of an apparatus for obtaining video coding compression quality according to the present invention
  • FIG. 11 is a block diagram of a first embodiment of a terminal according to the present invention.
  • Figure 12 is a block diagram of a second embodiment of a terminal of the present invention
  • Figure 13 is a block diagram of an embodiment of a server of the present invention.
  • the method of the embodiment of the present invention may be applied to the sending end of the sending video stream, and may also be applied to the network side of the transport video stream, and may also be applied to the receiving end of the receiving video stream.
  • the method may include:
  • Step 101 Acquire video stream information, where the video stream information includes a video frame type, a video frame size, a frame rate, and a code rate.
  • video stream information is first obtained, and the information may include a video frame type and size, a frame rate, and a code rate.
  • the information may include a video frame type and size, a frame rate, and a code rate.
  • other information such as a video frame quantization parameter, may also be included.
  • the video frame type may specifically determine an I frame (wherein the I frame refers to an intra-coded frame of the video) and a P frame by using a size of the video frame in the video stream (wherein the P frame refers to the video)
  • the interframe coding frame can also be obtained by an existing frame type detection method, or by parsing a code stream or the like.
  • the size of the video frame in the video stream may be a byte, a bit, or a kilobit.
  • the unit of the code rate is kilobits per second (Kbps)
  • the video frame size is kilobit (Kbit).
  • the frame rate can be preset or obtained through network transmission. It can also be derived from the RTP timestamp.
  • the RTP timestamp is calculated by the clock frequency to represent the time.
  • the frame rate clock frequency I is displayed in the order of two adjacent
  • the increment of RTP timestamp between frames, usually, the clock frequency of the video is 90,000.
  • the code rate is the amount of video data per second. For details, please refer to the description of the subsequent embodiments.
  • Step 102 Calculate the complexity of the video content according to the video stream information, where the complexity of the video content includes time complexity or space complexity or time complexity and space complexity.
  • the video content complexity may include only time complexity or spatial complexity, or may include two kinds of complexity at the same time.
  • the I frame size in the video frame may be specifically determined.
  • determining the code rate obtained in the previous step when the video frame information further includes the video frame quantization parameter information, determining the number of bits corresponding to each pixel of the P frame corresponding to the quantization parameter; when calculating the space complexity, Specifically, it may be determined according to the P frame size in the video frame and the code rate obtained in the previous step, or when the video stream information further includes video frame quantization parameter information, according to the bit corresponding to each pixel of the I frame corresponding to the quantization parameter. The number is determined.
  • Step 103 Calculate video coding compression quality according to the code rate, the frame rate, and the complexity of the video content. After obtaining the code rate, the frame rate, and the complexity of the video content, the video coding compression quality may be directly determined according to the three. The video encoding compression distortion may also be first determined according to the code rate and the video content complexity, and then the compression quality of the video encoding is determined according to the video encoding compression distortion and the frame rate.
  • the video coding compression quality is the basis for accurately evaluating the quality of the entire video stream.
  • the quality of the network video can be evaluated based on the compression quality of the video coding.
  • the compression quality of the general video coding is high, and the quality of the network video is also high.
  • the embodiment of the present invention only needs to obtain the video frame information, the code rate, the frame rate, and the video content complexity of the video stream to obtain the video coding compression quality, and the process does not need to obtain the entire original reference video and the terminal video. There is no need to deeply resolve the specific MV or residual value of the video stream, which greatly reduces the complexity of video quality assessment and enables real-time evaluation. At the same time, due to the influence of video content characteristics (ie, video content complexity) and frame rate, the quality of the encoded compression is more in line with the subjective feelings of the human eye.
  • FIG. 2 is a flow chart of a second embodiment of a method for obtaining video coding compression quality according to the present invention. This embodiment is described by using the network side of the video stream or the receiving end of the video stream as an example.
  • the method may include:
  • Step 201 Acquire video stream information in a predetermined time period, where the video stream information includes an I frame size, a frame rate, and a total data volume of the video stream.
  • the video stream in a certain period of time is first received, and the time period is MT, and then the information in the video stream is obtained:
  • an I frame in the video stream by using a size of the video frame or parsing the code stream, and further obtaining the size of the I frame; obtaining a preset frame rate or obtaining a frame rate according to the RTP timestamp, where the frame rate is recorded as fps;
  • ⁇ RTPpayloadSize (indicating the total amount of data payload of the video packet) or ⁇ ⁇ S (representing the total amount of data in the video frame).
  • the amount of data lost may be inferred according to the amount of data of the received data packet or video frame. There may be multiple methods, such as considering that the size of the lost packet is equal to the size of the previous correctly received packet, or the loss of the video frame. The size is equal to the size of the previous correct received frame.
  • Step 202 Calculate a ratio of a total data volume of the video stream to a time period to obtain a code rate.
  • the code rate is MT or MT and the unit is Kbps.
  • a function of the ratio of the total data amount of the video stream to the time period can also be used as the code rate.
  • Step 203 Calculate the corrected code rate according to the code rate and the frame rate.
  • the code rate obtained by the above calculation can be corrected according to the frame rate to obtain the corrected code rate.
  • the process of obtaining the corrected code rate may include the following steps 301 302:
  • Step 301 Determine a smaller value between a frame rate obtained from the video stream and a reference frame rate.
  • the frame rate 30 can be used as a reference, that is, the reference frame rate can be 30.
  • the reference frame rate can be 30.
  • other values can be selected as needed.
  • m "( , , 3 () ) is obtained. Step 302, determining a corrected code rate based on a ratio of the calculated code rate to the smaller value.
  • This step 203 can be performed again when it is necessary to use the corrected code rate, and is not limited to the sequence of steps in this embodiment. In other embodiments, the step 203 may not be included, that is, after the code rate is obtained, the subsequent calculation is performed directly according to the code rate without using the corrected code rate.
  • Step 204 Determine a time complexity according to a ratio of a code rate and an I frame size.
  • the subjective experience of different code streams at the same code rate is also greatly different due to the complexity of the video content, that is, the time and space complexity.
  • the time content complexity is taken as an example for description.
  • a sequence with a large time complexity is generally larger than a P/B frame of a sequence with a small time complexity, and an average I frame is smaller, so the code rate Br and The ratio of the average I frame size can reflect the time complexity of one of the characteristics of the video content to a certain extent, and the time complexity is recorded as TCC.
  • the method for determining the time complexity may specifically include the following steps: 401 402:
  • Step 401 Determine an average I frame size within a predetermined time period according to the I frame size.
  • all I frames of the video stream in a predetermined time period can be acquired, and then all I frame sizes are flat.
  • the - ⁇ - mean is determined as the average I frame size, and some I frames can also be selected to calculate the average.
  • the average I frame size is recorded as ABI.
  • Step 402 Determine a time complexity according to a ratio of a code rate to an average I frame size.
  • Step 205 Calculate video coding compression distortion according to the modified code rate, time complexity, and video quality evaluation parameters.
  • the distortion can be calculated according to the following formula:
  • VDc is the video encoding compression distortion
  • MOS is the video quality evaluation parameter
  • MOSmax is the maximum value of the video quality evaluation parameter, which represents the highest score of the video (if the score is five points, it is 5)
  • MOSmin is the video quality evaluation parameter.
  • ai , a 2 , a 3 and a 4 are constants.
  • Video encoding compression quality can also be obtained directly in accordance with the modified code rate and time complexity in another embodiment.
  • step 203 if step 203 is not performed, that is, the code rate obtained in step 202 is not corrected, video coding compression distortion or video coding compression quality may be directly obtained according to code rate and time complexity.
  • Step 206 Calculate video coding compression quality according to video coding compression distortion and frame rate.
  • the video coding compression quality is the difference between the maximum value of the video quality evaluation parameter and the video coding compression distortion.
  • the video encoding compression quality can be calculated according to the following formula:
  • the result can also be replaced by a lookup table, for example, fpS ).
  • the video encoding compression quality can measure the quality of the video]
  • the embodiment of the present invention does not need to obtain the complete original reference video and the complete terminal video, and does not need to perform complete deep analysis on the video stream, and only needs to obtain the code rate and frame rate information of the video stream to obtain the video coding compression quality, complete the video.
  • the quality assessment, the evaluation complexity is low, so real-time evaluation can also be realized;
  • the method considers the influence of the frame rate and the time complexity in the video content characteristics, and is more in line with the human visual system's perception of the coding compression distortion.
  • FIG. 5 it is a flowchart of a third embodiment of a method for obtaining video coding compression quality according to the present invention.
  • This embodiment is still described by using the network side for transmitting a video stream or the receiving end for receiving a video stream as an example.
  • the difference between this embodiment and the previous embodiment is that, in the above embodiment, the obtained video coding compression quality only considers the influence of the time complexity in the video content complexity, and further considers the video content complexity in this embodiment. Another characteristic of degrees is the effect of spatial complexity.
  • the method can include:
  • Step 501 Obtain a frame type, a frame size, a frame rate, a code rate, a modified code rate, and a time complexity of the video stream in the predetermined time period.
  • the I frame and the P frame in the video stream can be obtained by the size of the video frame or the parsing code stream, and the size of the I frame and the P frame are further obtained.
  • the obtaining of the frame rate fps, the code rate BR, the modified frame rate MBR, and the time complexity TCC in this step is similar to the step 201 204 in the foregoing embodiment, and details are not described herein again.
  • Step 502 Determine a spatial complexity according to a ratio of a code rate and a P frame size.
  • the sequence with large spatial complexity is generally larger than the average I frame of the sequence with small spatial complexity, and the P/B frame is smaller, so the code rate Br
  • the ratio of the average P frame size to a certain extent can reflect the content characteristics of the video, that is, the spatial complexity, and the space complexity is recorded as SCC.
  • the method for determining the spatial complexity may specifically include the following steps: 601 602:
  • Step 601 Determine an average P frame size in a predetermined time period according to the P frame size.
  • the method for calculating the average P frame size in this step is similar to the method for calculating the average I frame size in step 401 in the foregoing embodiment, and details are not described herein again.
  • the average P frame size is recorded as ABP.
  • Step 602 Determine spatial complexity according to a ratio of a code rate to an average P frame size. Count: Where bo is a constant.
  • Step 503 Calculate video coding compression distortion according to the modified code rate, time, spatial complexity, and video quality evaluation parameters.
  • Video with time complexity or spatial complexity or time complexity and large spatial complexity has greater compression distortion at the same bit rate.
  • the calculation of video coding compression distortion can be based on the following formula:
  • VDc is the video coding compression distortion
  • M0S is the video quality evaluation parameter.
  • MOS max is the maximum value of the video quality evaluation parameter, which represents the highest score of the video (if the score is 5 points, it is 5)
  • MOS mm is the video quality.
  • Step 504 Calculate video coding compression quality according to video coding compression distortion and frame rate.
  • the video coding compression quality can be obtained by the same formula as in the step 206 in the foregoing embodiment.
  • the embodiment of the invention obtains the code rate and frame rate information of the video stream to obtain the video coding compression quality, completes the evaluation of the video quality, and has low evaluation complexity, so that real-time evaluation can also be realized; Moreover, the method considers the frame rate and the video. The influence of the time and space complexity of the content characteristics is more in line with the perception of the coding compression distortion by the human visual system.
  • only the influence of the spatial complexity SCC may be considered when obtaining the video coding compression distortion, regardless of the spatial complexity TCC.
  • the calculation of the video coding compression distortion may be based on the following formula:
  • Fi, f 2 f 3 and P f 4 are constants.
  • the corresponding video coding compression quality can be calculated by using the same formula as in step 206 in the foregoing embodiment.
  • FIG. 7 a flowchart of a fourth embodiment of a method for obtaining a video coding compression quality j: is shown.
  • This embodiment is still applied to the network side for transmitting a video stream or the receiving end for receiving a video stream as an example.
  • the difference between this embodiment and the previous embodiment is that the method for obtaining video content complexity, that is, time and space complexity, is different from the foregoing embodiment.
  • the method can include:
  • Step 701 Obtain a frame type, a frame rate, a code rate, a modified code rate, and a video frame quantization parameter of the video stream in the predetermined time period.
  • the I frame and the P frame in the video stream can be obtained by the size of the video frame or the parsing code stream, and the size of the I frame and the P frame are further obtained.
  • the obtaining of the frame rate fps, the code rate BR, and the modified frame rate MBR in this step is similar to the step 201 203 in the foregoing embodiment, and details are not described herein again.
  • the quantization parameter is an important parameter of the encoding process.
  • the setting of this parameter determines the encoding quality of the video image. The larger the QP, the worse the video image quality.
  • the specific QP value can be obtained by parsing the video stream.
  • Step 702 calculating time complexity.
  • the average number of bits per pixel of the P frame (indicated as ABPP) can reflect the time complexity.
  • the determined time complexity can include: Calculating a number of bits of each pixel of the P frame under the video frame quantization parameter according to the video frame type;
  • the time complexity is calculated based on the number of bits of each pixel of the P frame and the first parameter corresponding to the quantization parameter of the video frame.
  • time complexity can be calculated according to the following formula:
  • ! ⁇ And! ⁇ is the first parameter related to QP, that is, each QP value corresponds to a group! ⁇ And! ⁇ .
  • the calculation of the time complexity of the video stream can also be obtained in two ways, but not limited to the two methods. First, a TCC is calculated according to the QP and ABPP of each P frame, and then the video is obtained by the average value calculation method. The TCC of the stream; the second is to count the average value of the QP of each P frame of the video stream and the average value of the ABPP, and then calculate the TCC of the video stream by using the above formula.
  • the calculation of the time complexity of a specific single frame refer to the description of the patent entitled "A Video Quality Evaluation Method, System and Apparatus" with the application number of 200910161628.9 and the announcement number of CN101635846B.
  • Step 703 calculating space complexity.
  • the average number of bits per pixel (ABIP) of the I frame can reflect the spatial complexity.
  • the process of calculating the space complexity can include:
  • the spatial complexity can be calculated according to the following formula:
  • ⁇ and ⁇ 2 are the second parameters related to QP, that is, each QP value corresponds to a set of ⁇ and ⁇ 2 .
  • the calculation of the spatial complexity of the video stream can also be obtained in two ways, but not limited to the two methods.
  • One is to calculate an SCC according to the QP and ABIP of each I frame, and then calculate the average value. Obtaining the SCC of the video stream; second, counting the average value of the QP of each I frame of the video stream and the average value of the ABIP, and then calculating the SCC of the video stream by using the above formula.
  • the time complexity calculation of a specific single frame is described in the patent application number 200910161628.9, the publication number is CN101635846B, and the name is "a video quality evaluation method, system and device".
  • steps 702 and 703 may be reversed or may be performed simultaneously.
  • Step 704 Calculate video coding compression distortion according to the modified code rate, time, spatial complexity, and video quality evaluation parameters.
  • Step 705 Calculate video coding compression quality according to video coding compression distortion and frame rate.
  • the calculation of the video coding compression distortion and the video coding compression quality in steps 704 and 705 can be obtained by referring to the method of step 503 504 in the foregoing embodiment.
  • the calculation of the video coding compression distortion and the video coding compression quality may be performed only by the TCC or the SCC.
  • the specific process refer to the corresponding description in the foregoing embodiment, and details are not described herein.
  • the embodiment of the invention reduces the evaluation complexity and thus enables real-time evaluation; moreover, the method considers the influence of the frame rate and the temporal and spatial complexity of the video content characteristics, and is more in line with the perception of the coding compression distortion by the human visual system.
  • FIG. 8 is a flowchart of a fifth embodiment of a method for obtaining video coding compression quality according to the present invention. This embodiment is still described by using the network side for transmitting a video stream or the receiving end for receiving a video stream as an example.
  • the method can include:
  • Step 801 Obtain a frame type and a video frame quantization parameter of the video stream in the predetermined time period.
  • the I frame and the P frame in the video stream can be obtained by the size of the video frame or the parsed code stream, and the quantization parameter QP of the video frame in the video stream is obtained.
  • Step 802 Calculate a basic distortion of the video coding compression of the video stream according to the average video frame quantization parameter of the video stream.
  • the quantization step size (QPstep) can be obtained according to QP, and then the basic distortion of video coding compression is calculated by QPstep through table lookup or formula, which can be obtained by the following formula:
  • VD c ' (MOS max _MOU/ cl( ⁇ ) or
  • VD C ' (MOS max - MOS mm ) Where /M " cl ⁇ P ) is a function proportional to QP and is a function proportional to QPstep, and is between 0 and 1.
  • Step 803 Calculate a time complexity according to the average number of bits per pixel of the P frame under the quantization parameter of the video frame; calculate a spatial complexity according to the average number of bits of each pixel of the I frame under the quantization parameter of the video frame.
  • step 702 703 This step is the same as step 702 703 in the foregoing embodiment, and details are not described herein again. Getting time complexity
  • the next step 804 can be performed.
  • Step 804 correcting the basic distortion of the video coding compression according to the time complexity and the spatial complexity, and calculating the video coding compression distortion.
  • the correction process can use the function " ⁇ 71 ⁇ ' ⁇ ) based on time complexity and space complexity to correct the basic distortion of video coding compression. Specifically, the following formula can be used:
  • the calculation of the video coding compression quality can be obtained by referring to the method of step 504 in the foregoing embodiment.
  • the embodiment of the invention obtains the code rate and frame rate information of the video stream to obtain the video coding compression quality, completes the evaluation of the video quality, and has low evaluation complexity, so that real-time evaluation can also be realized; Moreover, the method considers the frame rate and the video. The influence of time and space complexity of content characteristics is more in line with the human visual system for coding compression loss. Really aware.
  • only the spatial complexity SCC or the time complexity TCC may be considered when obtaining the video coding compression quality, that is, only the function of the spatial complexity is used to correct the basic distortion of the video coding compression, or only The time complexity function is used to correct the basic distortion of the video coding compression, and then the video coding compression quality is determined after the video coding compression distortion is obtained.
  • the order of the steps in the above embodiments may be adjusted as needed, and is not limited to the above sequence of steps.
  • the above method embodiments may be applied to the network side of the transmission video stream, or applied to the receiving end of the received video stream for video quality evaluation.
  • the foregoing method embodiments may also be applied to the transmitting end of the video stream, and the difference between the application and the application on the network side and the receiving end is only that, in the video stream information obtained by the sending end, there is no video data packet or video frame loss.
  • the total amount of data in the video stream is equal to the total amount of data payloadd by the video packet to be transmitted or the total amount of data in the video frame.
  • the techniques in the embodiments of the present invention can be implemented by means of software plus a necessary general hardware platform. Based on such understanding, the technical solution in the embodiments of the present invention may be embodied in the form of a software product in essence or in the form of a software product, which may be stored in a storage medium such as a ROM/RAM. , a disk, an optical disk, etc., including instructions for causing a computer device (which may be a personal computer, server, or network device, etc.) to perform the methods described in various embodiments of the present invention or portions of the embodiments.
  • a computer device which may be a personal computer, server, or network device, etc.
  • the above is a description of the embodiment of the method of the present invention.
  • the apparatus for implementing the above method will be described below. Referring to FIG. 9, a block diagram of a first embodiment of an apparatus for obtaining video coding compression quality is provided.
  • the device can include:
  • the information acquiring unit 901 is configured to acquire video stream information, where the video stream information includes a video frame type, a video frame size, a frame rate, and a code rate.
  • the complexity calculation unit 902 is configured to calculate video content complexity according to the video stream information acquired by the information acquiring unit 901, where the video content complexity includes time complexity or space complexity or time complexity and space complexity;
  • the quality evaluation unit 903 is configured to calculate a video encoding compression quality according to the code rate acquired by the information acquiring unit 901, the frame rate, and the video content complexity obtained by the complexity calculating unit 902.
  • the information obtaining unit 901 first obtains video stream information, which may include a video frame type and size, a frame rate, and a code rate. Of course, it may also include other information, such as a video frame quantization parameter, etc., and the complexity calculation unit 902 according to the video stream information. Determining the complexity of the video content, which may include time complexity or Spatial complexity or time complexity and spatial complexity, when calculating the time complexity, may be determined according to the I frame size in the video frame and the code rate obtained in the previous step, or may also include the video frame quantization parameter in the video stream information.
  • the information is determined according to the number of bits corresponding to each pixel of the P frame corresponding to the quantization parameter; when calculating the spatial complexity, it may be determined according to the P frame size and the code rate in the video frame, or may be used in the video stream information.
  • the quality evaluation unit 903 can determine the video coding compression quality according to the code rate, the frame rate, and the video content complexity; or first, determine the video coding compression distortion according to the code rate and the video content complexity, and then compress the distortion according to the video coding.
  • the frame rate determines the compression quality of the video encoding.
  • the video encoding compression quality is obtained by using the foregoing unit, and the apparatus does not need to obtain the entire original reference video and the terminal video, and does not need to deeply parse the specific MV or residual value of the video stream, thereby greatly reducing the video quality.
  • the complexity of the assessment can be assessed in real time. At the same time, due to the influence of video content characteristics (ie, video content complexity) and frame rate, the quality of the encoded compression is more in line with the subjective perception of the human eye.
  • FIG. 10 it is a block diagram of a second embodiment of a video encoding compression quality evaluation apparatus according to the present invention.
  • the apparatus may further include a code rate correction unit 1004 in addition to the information acquisition unit 1001, the complexity calculation unit 1002, and the quality evaluation unit 1003.
  • the information acquiring unit 1001 may include: a code rate acquiring subunit configured to acquire a total data volume of the video stream in a predetermined time period; and determining a code according to a ratio of the total data volume of the video stream to the predetermined time period. rate.
  • the complexity calculation unit 1002 may include:
  • the first time sub-unit 1021 is configured to: when the video content complexity includes a time complexity, calculate an average I frame size in the predetermined time period according to the video frame type and size acquired by the information acquiring unit; And determining the time complexity according to a ratio of the code rate to the size of the average I frame;
  • a first space sub-unit 1022 configured to calculate an average P frame size in the predetermined time period according to the video frame type and size acquired by the information acquiring unit, when the video content complexity includes spatial complexity; And determining the spatial complexity according to a ratio of the code rate to the size of the average P frame.
  • the rate correcting unit 1004 is configured to calculate, according to the code rate and the frame rate, before the quality estimating unit 1003 determines the video encoding compression quality according to the code rate, the frame rate, and the video content complexity.
  • the corrected code rate; the code rate correction unit 1004 may further include:
  • the quality evaluation unit 1003 is specifically configured to determine a video coding compression quality according to the corrected code rate acquired by the code rate modification unit 1004, the frame rate, and the video content complexity.
  • the quality assessment unit 1003 can include:
  • a distortion calculation sub-unit 1031 configured to determine a video coding compression distortion according to the corrected code rate obtained by the code rate correction unit, the video content complexity, and the video quality evaluation parameter;
  • the evaluation sub-unit 1032 is configured to determine the video coding compression quality according to the video coding compression distortion and the frame rate.
  • the evaluation sub-unit 1032 is specifically configured to: when the frame rate is greater than or equal to 24, use a difference between a maximum value of the video quality evaluation parameter and the video coding compression distortion as the video coding compression quality; When the rate is less than or equal to 24, the difference between the maximum value of the video quality evaluation parameter and the video coding compression distortion is corrected based on the video content complexity, and the corrected result is used as the video coding compression quality in the present invention.
  • the complexity calculation unit may include:
  • a second time subunit configured to: when the video stream information acquired by the information acquiring unit further includes a video frame quantization parameter, and the video content complexity includes a time complexity, calculate the video frame according to the video frame type Quantizing the number of bits of each pixel of the P frame under the parameter; and calculating the time complexity according to the number of bits of each pixel of the P frame and the first parameter corresponding to the quantization parameter of the video frame;
  • a second spatial subunit configured to: when the video stream information acquired by the information acquiring unit further includes a video frame quantization parameter, and the video content complexity includes a spatial complexity, calculate the video frame according to the video frame type Quantizing the number of bits of each pixel of the I frame under the parameter; and calculating the spatial complexity according to the number of bits of each pixel of the I frame and the second parameter corresponding to the quantization parameter of the video frame.
  • the video encoding quality can also be obtained by the above-described rate correcting unit 1004 and quality evaluating unit 1003.
  • the video encoding compression quality is obtained by using the foregoing unit, and the apparatus does not need to obtain the entire original reference video and the terminal video, and does not need to deeply parse the specific MV or residual value of the video stream, thereby greatly reducing the video quality.
  • the complexity of the assessment can be assessed in real time. At the same time, due to the influence of video content characteristics (ie, video content complexity) and frame rate, the quality of the encoded compression is more in line with the subjective perception of the human eye.
  • FIG. 11 a block diagram of a first embodiment of a terminal according to the present invention is shown.
  • the terminal may include a first transceiver device 1101 and a first processor 1102.
  • the first transceiver device 1101 is configured to receive a video stream.
  • the first processor 1102 is configured to acquire video stream information in a video stream received by the first transceiver device 1101, where the video stream information includes a video frame type, a video frame size, a frame rate, and a code rate.
  • the video stream information calculates a video content complexity, where the video content complexity includes time complexity or spatial complexity or time complexity and spatial complexity; and is calculated according to the code rate, the frame rate, and the complexity of the video content. Video encoding compression quality.
  • the terminal can be set at the receiving end of the video stream to obtain the video encoding compression quality, and the terminal greatly reduces the complexity of the video quality assessment, and can be evaluated in real time.
  • the quality of the encoded compression is more in line with the subjective feelings of the human eye.
  • FIG. 12 it is a block diagram of a second embodiment of a terminal according to the present invention.
  • the terminal may include a second transceiver 1201 and a second processor 1202.
  • the second transceiver 1201 is configured to send a video stream.
  • the second processor 1202 is configured to acquire video stream information in a video stream sent by the second transceiver device 1201, where the video stream information includes a video frame type, a video frame size, a frame rate, and a code rate.
  • the stream information calculates a video content complexity, the video content complexity including time complexity or space complexity or time complexity and spatial complexity; calculating a video according to the code rate, the frame rate, and the video content complexity Encoding compression quality.
  • the terminal can be set at the transmitting end of the video stream, thereby obtaining video encoding compression quality for use in subsequent video quality evaluation, and the terminal greatly reduces the complexity of the video quality assessment, and can perform real-time evaluation. .
  • the quality of the encoded compression is more in line with the subjective feelings of the human eye.
  • FIG. 13 a block diagram of an embodiment of a server of the present invention is shown.
  • the server is located on the network side and may include a third transceiver 1301 and a third processor 1302.
  • the third transceiver device 1301 is configured to transmit the video stream from the sending end to the receiving end.
  • the third processor 1302 is configured to acquire video stream information in a video stream that is transmitted by the third transceiver device 1301, where the video stream information includes a video frame type, a video frame size, a frame rate, and a code rate.
  • the stream information calculates a video content complexity, the video content complexity including time complexity or space complexity or time complexity and spatial complexity; calculating a video according to the code rate, the frame rate, and the video content complexity Encoding compression quality.
  • the server can be set on the network side for the transmission of the video stream, and the server has been obtained.
  • the frequency coded compression quality is used in subsequent video quality assessments, greatly reducing the complexity of video quality assessment and enabling real-time evaluation.
  • the quality of the encoded compression is more in line with the subjective feelings of the human eye.

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Abstract

本发明实施例公开了一种获得视频编码压缩质量的方法及装置。该方法可以包括:获取视频流信息,所述视频流信息包括视频帧类型、视频帧大小、帧率和码率;根据所述视频流信息计算视频内容复杂度,所述视频内容复杂度包括时间复杂度或空间复杂度或时间复杂度及空间复杂度;根据所述码率、所述帧率和所述视频内容复杂度计算视频编码压缩质量。本发明实施例只需要获得视频流的视频帧信息,码率,帧率和视频内容复杂度即可获得视频编码压缩质量,该视频编码压缩质量可供后续的视频质量评估中使用,该过程大大减小了视频质量评估的复杂度,能够实时进行评估。同时,由于考虑了视频内容特性(即视频内容复杂度)和帧率的影响,使评估出的编码压缩质量更符合人眼的主观感受。

Description

一种获得视频编码压縮质暈的方法及装置 本发明要求于 2012年 8月 21 日提交中国专利局、 申请号为 201210299000.7、发 明名称为 "一种获得视频编码压缩质量的方法及装置"的中国专利申请的优先权, 其 全部内容通过弓 I用结合在本发明中。
技术领域 本发明涉及数据处理技术领域,特别是涉及一种获得视频编码压缩质量的方法及 装置。 背景技术
随着网络技术的发展, 影视点播、 网络电视、 可视电话等已成为宽带网络的主要 业务, 并且这些业务也将成为第三代(3G, the 3rd Generation)无线网络的主要业务。 在网络视频迅速发展的背景下, 如何对网络视频的质量进行便捷、有效的评估, 便成 为网络视频应用中一个迫切需要解决的重要问题。
现有技术中网络视频质量评估方法包括全参考视频质量评估方法,该方法采用计 算峰值信噪比 (PS R, Peak Signal to Noise Ratio) 的方式评估视频质量, 其方法流 程大致包括: 获取原始参考视频以及终端视频; 对原始参考视频以及终端视频进行对 比计算 PS R; 根据 PSNR的具体数值确定视频质量。
然而, 该方法需要获取完整的原始参考视频以及终端视频, 将视频流进行完全深 层的解析, 评估复杂度太高, 使得视频质量评估不能实时进行。 发明内容 本发明实施例中提供了一种获得视频编码压缩质量的方法及装置,能够降低评估 的复杂度, 可以使视频质量评估实时进行, 以解决现有技术中的问题。
为了解决上述技术问题, 本发明实施例公开了如下技术方案:
一方面, 本发明实施例提供了一种获得视频编码压缩质量的方法, 包括: 获取视频流信息, 所述视频流信息包括视频帧类型、 视频帧大小、 帧率和码率; 根据所述视频流信息计算视频内容复杂度,所述视频内容复杂度包括时间复杂度 或空间复杂度或时间复杂度及空间复杂度;
根据所述码率、 所述帧率和所述视频内容复杂度计算视频编码压缩质量。
进一步, 所述获取视频流信息包括:
获取所述的视频帧类型、 视频帧大小和帧率; 以及
根据所述视频流总数据量与所述预定时间段的比值确定码率。
进一步,所述视频流总数据量为接收到的视频流数据量与丢失的视频流数据量之 禾口。
进一步, 当所述视频内容复杂度包括时间复杂度时, 所述根据所述视频流信息计 算视频内容复杂度包括:
根据所述视频帧类型及大小计算所述预定时间段内的平均 I帧大小;
根据所述码率与所述平均 I帧的大小的比值确定所述时间复杂度;
当所述视频内容复杂度包括空间复杂度时,所述根据所述视频流信息计算视频内 容复杂度包括:
根据所述视频帧类型及大小计算所述预定时间段内的平均 P帧大小; 根据所述码率与所述平均 P帧的大小的比值确定所述空间复杂度。
进一步, 所述时间复杂度具体为:
Figure imgf000004_0001
其中, TCC为时间复杂度, BR为码率, ABI为平均 I帧大小, aQ为常数。 当所述视频内容复杂度包括时间复杂度时,所述根据所述视频流信息计算视频内 容复杂度包括:
根据所述视频帧类型计算所述视频帧量化参数下 P帧的每个像素的比特数; 根据所述 P帧的每个像素的比特数以及所述视频帧量化参数对应的第一参量,计 算所述时间复杂度;
当所述视频内容复杂度包括空间复杂度时,所述根据所述视频流信息计算视频内 容复杂度包括:
根据所述视频帧类型计算所述视频帧量化参数下 I帧的每个像素的比特数; 根据所述 I帧的每个像素的比特数以及所述视频帧量化参数对应的第二参量, 计 算所述空间复杂度。 进一步, 在所述根据所述码率、所述帧率及所述视频内容复杂度计算视频编码压 缩质量之前, 还包括:
根据所述码率及所述帧率计算修正的码率;
所述根据所述码率、所述帧率及所述视频内容复杂度计算视频编码压缩质量, 包 根据所述修正的码率、 所述帧率及所述视频内容复杂度计算视频编码压缩质 进一步, 所述根据所述码率及所述帧率计算修正的码率, 包括:
确定获取的所述帧率与参考帧率之间的较小值;
根据所述码率与所述较小值的比值确定所述修正的码率。
进一步, 所述修正的码率具体为:
BR
MBR = - •30
Min(fps,30)
其中, MBR为修正的码率, BR为码率, fps为帧率, 30为参考帧率。
进一步, 所述根据所述修正的码率、所述帧率及所述视频内容复杂度计算视频编 码压缩质量, 包括:
根据所述修正的码率,所述视频内容复杂度, 以及视频质量评价参数计算视频编 码压缩失真;
根据所述视频编码压缩失真以及所述帧率计算所述视频编码压缩质量。
进一步, 当所述视频内容复杂度只包含时间复杂度时, 所述视频编码压缩失真具 体为:
Figure imgf000005_0001
其中, VDc为视频编码压缩失真, MOS为视频质量评价参数, MOSmax为视频 质量评价参数的最大值, MOSmm为视频质量评价参数的最小值, MBR为修正的码 率, TCC为时间复杂度, ai, a2, a3, a4为常数。
进一步,所述根据所述视频编码压缩失真以及所述帧率计算所述视频编码压缩质 量, 包括:
当所述帧率大于等于 24时, 将所述视频质量评价参数的最大值与所述视频编码 压缩失真的差值作为所述视频编码压缩质量;
当所述帧率小于等于 24时, 基于所述视频内容复杂度及所述帧率修正所述视频 质量评价参数的最大值与所述视频编码压缩失真的差值,将修正后的结果作为所述视
Figure imgf000006_0001
另一方面, 本发明实施例还提供一种获得视频编码压缩质量的装置, 包括: 信息获取单元, 用于获取视频流信息, 所述视频流信息包括视频帧类型、视频帧 大小、 帧率和码率;
复杂度计算单元,用于根据所述信息获取单元获取的视频流信息计算视频内容复 杂度, 所述视频内容复杂度包括时间复杂度或空间复杂度或时间复杂度及空间复杂 度;
质量评估单元, 用于根据所述信息获取单元获取的码率、所述帧率和所述复杂度 计算单元获得的视频内容复杂度计算视频编码压缩质量。
进一步, 所述信息获取单元包括:
码率获取子单元, 用于获取预定时间段内的视频流总数据量; 并根据所述视频流 总数据量与所述预定时间段的比值确定码率。
进一步, 所述复杂度计算单元包括:
第一时间子单元, 用于当所述视频内容复杂度包括时间复杂度时, 根据所述信息 获取单元获取的所述视频帧类型及大小计算所述预定时间段内的平均 I帧大小; 并根 据所述码率与所述平均 I帧的大小的比值确定所述时间复杂度;
第一空间子单元, 用于当所述视频内容复杂度包括空间复杂度时, 根据所述信息 获取单元获取的所述视频帧类型及大小计算所述预定时间段内的平均 P帧大小;并根 据所述码率与所述平均 P帧的大小的比值确定所述空间复杂度。
进一步, 所述复杂度计算单元包括:
第二时间子单元,用于当所述信息获取单元获取的视频流信息还包括视频帧量化 参数, 且所述视频内容复杂度包括时间复杂度时,根据所述视频帧类型计算所述视频 帧量化参数下 P帧的每个像素的比特数;并根据所述 P帧的每个像素的比特数以及所 述视频帧量化参数对应的第一参量, 计算所述时间复杂度;
第二空间子单元,用于当所述信息获取单元获取的视频流信息还包括视频帧量化 参数, 且所述视频内容复杂度包括空间复杂度时,根据所述视频帧类型计算所述视频 帧量化参数下 I帧的每个像素的比特数; 并根据所述 I帧的每个像素的比特数以及所 述视频帧量化参数对应的第二参量, 计算所述空间复杂度。
进一步, 还包括:
码率修正单元, 用于在所述质量评估单元根据所述码率、所述帧率及所述视频内 容复杂度确定视频编码压缩质量之前, 根据所述码率及所述帧率计算修正的码率; 所述质量评估单元, 具体用于根据所述码率修正单元获取的修正的码率、所述帧 率及所述视频内容复杂度计算视频编码压缩质量。
进一步, 所述码率修正单元包括:
比较子单元,用于确定所述信息获取单元获取的所述帧率与参考帧率之间的较小 值;
计算子单元, 用于根据所述码率与所述较小值的比值确定所述修正的码率。 进一步, 所述质量评估单元包括:
失真计算子单元, 用于根据所述码率修正单元获得的修正的码率,所述视频内容 复杂度, 以及视频质量评价参数计算视频编码压缩失真;
评估子单元,用于根据所述视频编码压缩失真以及所述帧率计算所述视频编码压 缩质量。
进一步, 所述评估子单元, 具体用于当所述帧率大于等于 24时, 将所述视频质 量评价参数的最大值与所述视频编码压缩失真的差值作为所述视频编码压缩质量;当 所述帧率小于等于 24时, 基于所述视频内容复杂度修正所述视频质量评价参数的最 大值与所述视频编码压缩失真的差值, 将修正后的结果作为所述视频编码压缩质量。
另一方面, 本发明实施例还提供一种终端, 包括第一收发装置及第一处理器, 所述第一收发装置, 用于接收视频流;
所述第一处理器, 用于在所述第一收发装置接收到的视频流中获取视频流信息, 所述视频流信息包括视频帧类型、视频帧大小、 帧率和码率; 根据所述视频流信息计 算视频内容复杂度,所述视频内容复杂度包括时间复杂度或空间复杂度或时间复杂度 及空间复杂度; 根据所述码率、所述帧率和所述视频内容复杂度计算视频编码压缩质 另一方面, 本发明实施例还提供一种终端, 包括第二收发装置及第二处理器, 所述第二收发装置, 用于发送视频流;
所述第二处理器, 用于在所述第二收发装置发送的视频流中获取视频流信息, 所 述视频流信息包括视频帧类型、视频帧大小、帧率和码率; 根据所述视频流信息计算 视频内容复杂度,所述视频内容复杂度包括时间复杂度或空间复杂度或时间复杂度及 空间复杂度;根据所述码率、所述帧率和所述视频内容复杂度计算视频编码压缩质量。 另一方面, 本发明实施例还提供一种服务器, 位于网络侧, 所述服务器包括第三 收发装置及第三处理器,
所述第三收发装置, 用于将视频流从发送端传输至接收端;
所述第三处理器, 用于在所述第三收发装置传输的视频流中获取视频流信息, 所 述视频流信息包括视频帧类型、视频帧大小、帧率和码率; 根据所述视频流信息计算 视频内容复杂度,所述视频内容复杂度包括时间复杂度或空间复杂度或时间复杂度及 空间复杂度;根据所述码率、所述帧率和所述视频内容复杂度计算视频编码压缩质量。
本发明实施例只需要获得视频流的视频帧信息, 码率, 帧率和视频内容复杂度即 可获得视频编码压缩质量, 以可在后续的视频质量评估中使用, 该过程既不需要获得 整个原始参考视频以及终端视频, 也不需要深层解析视频码流的具体 MV或残差值, 大大减小了视频质量评估的复杂度, 能够实时进行评估。 同时, 由于考虑了视频内容 特性(即视频内容复杂度)和帧率的影响, 使评估出的编码压缩质量更符合人眼的主 观感受。 附图说明 为了更清楚地说明本发明实施例或现有技术中的技术方案,下面将对实施例或现 有技术描述中所需要使用的附图作简单地介绍, 显而易见地,对于本领域普通技术人 员而言, 在不付出创造性劳动性的前提下, 还可以根据这些附图获得其他的附图。
图 1为本发明一种获得视频编码压缩质量的方法的第一实施例流程图; 图 2为本发明一种获得视频编码压缩质量的方法的第二实施例流程图; 图 3为图 2所示实施例中获得修正码率的方法流程图;
图 4为图 2所示实施例中获得时间复杂度的方法流程图;
图 5为本发明一种获得视频编码压缩质量的方法的第三实施例流程图; 图 6为图 5所示实施例中获得空间复杂度的方法流程图;
图 7为本发明一种获得视频编码压缩质量的方法的第四实施例流程图; 图 8为本发明一种获得视频编码压缩质量的方法的第五实施例流程图; 图 9为本发明一种获得视频编码压缩质量的装置的第一实施例框图;
图 10为本发明一种获得视频编码压缩质量的装置的第二实施例框图; 图 11为本发明一种终端的第一实施例框图;
图 12为本发明一种终端的第二实施例框图; 图 13为本发明一种服务器的实施例框图。 具体实施方式 为了使本技术领域的人员更好地理解本发明实施例中的技术方案,并使本发明实 施例的上述目的、特征和优点能够更加明显易懂, 下面结合附图对本发明实施例中技 术方案作进一步详细的说明。
参见图 1, 为本发明一种获得视频编码压缩质量的方法的第一实施例流程图。 本发明实施例方法可以应用于发送视频流的发送端,也可以应用于传输视频流的 网络侧, 还可以应用于接收视频流的接收端, 该方法可以包括:
步骤 101, 获取视频流信息, 所述视频流信息包括视频帧类型、 视频帧大小、 帧 率和码率。
在本发明实施例中, 首先获得视频流信息, 该信息可以包括视频帧类型及大小、 帧率和码率, 当然也还可以包括其他信息, 例如视频帧量化参数等。
其中, 视频帧类型具体可以通过该视频流中视频帧的大小来确定其中的 I帧(其 中, I帧指的是视频的帧内编码帧) 和 P帧 (其中, P帧指的是视频的帧间编码帧), 也可以由现有的帧类型检测方法, 或者通过解析码流等来得到帧类型。其中, 所述视 频流中视频帧的大小可以是字节(byte)、 比特 (bit)、 千比特(Kbit),当码率的单位为 千比特每秒 (Kbps) 时, 所述视频帧大小的单位为千比特 (Kbit) .
帧率可以是预先设定的, 或者通过网络传输得到; 还可以根据 RTP 时间戳推导 得到, RTP 时间戳是用时钟频率计算而来表示时间的, 帧率 = 时钟频率 I显示顺序 上相邻两帧之间 RTP timestamp的增量, 通常, 视频的时钟频率为 90000。 码率即每 秒的视频数据量, 具体计算请参见后续实施例的描述。
步骤 102, 根据视频流信息计算视频内容复杂度, 该视频内容复杂度包括时间复 杂度或空间复杂度或时间复杂度及空间复杂度。
在本发明方法实施例中, 该视频内容复杂度可以仅包括时间复杂度或空间复杂 度, 也可同时包含两种复杂度, 在计算时间复杂度时, 具体可以根据视频帧中的 I帧 大小以及上步骤获得的码率确定,也可以当视频流信息中还包括视频帧量化参数信息 时,根据该量化参数对应的 P帧的每个像素对应的比特数确定;在计算空间复杂度时, 具体可以根据视频帧中的 P帧大小以及上步骤获得的码率确定,也可以当视频流信息 中还包括视频帧量化参数信息时,根据该量化参数对应的 I帧的每个像素对应的比特 数确定。 具体请参照后续实施例的描述。 步骤 103, 根据所述码率、 所述帧率和所述视频内容复杂度计算视频编码压缩质 在获得码率、帧率以及视频内容复杂度后, 可以直接根据三者来确定视频编码压 缩质量; 也可以首先根据码率和视频内容复杂度确定视频编码压缩失真,然后根据该 视频编码压缩失真及帧率确定视频编码的压缩质量。
视频编码压缩质量是准确评估整个视频流质量的基础,基于该视频编码的压缩质 量即可评估网络视频的质量, 一般视频编码的压缩质量较高的, 网络视频的质量也较 高。
本发明实施例通过上述步骤只需要获得视频流的视频帧信息, 码率, 帧率, 视频 内容复杂度即可获得视频编码压缩质量,该过程既不需要获得整个原始参考视频以及 终端视频,也不需要深层解析视频码流的具体 MV或残差值,大大减小了视频质量评 估的复杂度, 能够实时进行评估。 同时, 由于考虑了视频内容特性(即视频内容复杂 度) 和帧率的影响, 使评估出的编码压缩质量更符合人眼的主观感受。
参见图 2, 为本发明一种获得视频编码压缩质量的方法的第二实施例流程图。 本实施例以应用于传输视频流的网络侧,或应用于接收视频流的接收端为例进行 说明, 该方法可以包括:
步骤 201, 获取预定时间段内的视频流信息, 该视频流信息包括 I帧大小、 帧率 和视频流总数据量。
本步骤中, 首先接收一定时间段内的视频流, 该时间段即为 MT, 然后获取该段 视频流中的信息:
通过视频帧的大小或解析码流获得该视频流中的 I帧,并进一步获得 I帧的大小; 获得预设的帧率或者根据 RTP时间戳获知帧率, 该帧率记为 fps;
根据接收到的视频数据包或视频帧推测是否存在丢失的数据包或视频帧, 若存 在, 则推测丢失的数据包或视频帧的数据量,然后计算接收到的数据包或视频帧的数 据量与丢失的数据量的和, 获得该 MT 内的视频流总数据量, 该总数据量记为
^ RTPpayloadSize (表示视频数据包净载总数据量)或者∑ ^^S (表示视频帧 的总数据量)。 其中, 丢失的数据量可以根据已接收到的数据包或视频帧的数据量来 推测, 其方法可以有多种, 比如认为丢失包的大小等于之前一个正确接收包的大小, 或者丢失视频帧的大小等于之前一个正确接收帧的大小。
当然, 也还可以通过其他方式获取上述视频流的信息, 此处不再一一列举。 步骤 202, 计算视频流总数据量与时间段的比值获得码率。 R TPpayloadSize Frame Size
BR = ^——― BR = ^
该码率 MT 或者 MT , 单位为 Kbps。
当然, 也可以将该视频流总数据量与时间段的比值的函数作为码率。
步骤 203, 根据码率及帧率计算修正的码率。
由于帧率降低可导致单帧画面质量升高, 因此, 在本实施例中, 还可以根据帧率 来对上述计算获得的码率进行修正, 获得修正的码率。 具体的, 获得修正的码率的过 程可以包括以下步骤 301 302:
步骤 301, 确定从视频流中获取的帧率与参考帧率之间的较小值。
因为人眼的视觉残留特性, 人眼不能分辨超过每秒 30帧的画面, 因此可以将帧 率 30做为基准, 也即参考帧率可以是 30, 当然也可以根据需要选择其他数值。进而, 获取较小值即 m"(/ ,3 ())。 步骤 302, 根据计算获得的码率与上述较小值的比值确定修正的码率。
MBR =——― 30
将修正的码率记为 MBR, 则 Mini ps;^ 。 在其他实施例中, 也可以 选取该比值的其他倍数或函数作为修正的码率。
该步骤 203可以在需要使用修正的码率时再执行,并不限定于本实施例中的步骤 顺序。 在其它实施例中, 也可以不包含该步骤 203, 也即在获得码率后, 直接根据码 率进行后续计算, 而无需采用修正的码率。
步骤 204, 根据码率及 I帧大小的比值确定时间复杂度。
当视频有编码压缩失真时, 由于视频内容复杂度即时间、 空间复杂度不同, 同一 码率下的不同码流的主观体验也有很大差异。尤其是在码率比较低的情况下, 内容丰 富的码流的主观体验比内容简单的码流的主观体验明显差很多。因此,在计算视频编 码压缩质量时, 需将视频内容复杂度考虑进去。本实施例中, 以时间内容复杂度为例 进行说明。
通过对大量码流数据的统计分析实验, 在一定码率下, 时间复杂度大的序列一般 比时间复杂度小的序列的 P/B帧大些, 平均 I帧小一些, 因此码率 Br与平均 I帧大 小的比值在一定程度上可以反映视频内容的特性之一即时间复杂度,该时间复杂度记 为 TCC。
该确定时间复杂度的方法具体可以包括以下步骤 401 402:
步骤 401, 根据 I帧大小确定预定时间段内的平均 I帧大小。
在本步骤中可以获取预定时间段内视频流的所有 I帧, 然后将所有 I帧大小的平 -ιο- 均值确定为平均 I帧大小,也可以选取部分 I帧计算平均值。将平均 I帧大小记为 ABI。
步骤 402, 根据码率与平均 I帧大小的比值确定时间复杂度。
算:
Figure imgf000012_0001
其中, aQ为常数。
步骤 205, 根据修正的码率,时间复杂度, 以及视频质量评价参数计算视频编码压 缩失真。
时间复杂度越大的视频, 在同一码率下的压缩失真越大, 具体的, 该失真的计算 可以依据以下公式:
Figure imgf000012_0002
VDc为视频编码压缩失真, MOS为视频质量评价参数, 其中, MOSmax为视频 质量评价参数的最大值, 代表视频的最高分 (如评分为五分制, 则为 5), MOSmin为 视频质量评价参数的最小值, 代表视频的最低分 (如评分为五分制, 则为 1), ai, a2, a3和 a4为常数。
在另一实施例中也可以直接根据修正的码率和时间复杂度获得视频编码压缩质 量。 在另一实施例中, 若不执行步骤 203, 也即不对步骤 202获得的码率进行修正, 也可以直接根据码率及时间复杂度获得视频编码压缩失真或视频编码压缩质量。
步骤 206, 根据视频编码压缩失真以及帧率计算视频编码压缩质量。
视频编码压缩质量为视频质量评价参数的最大值与视频编码压缩失真的差值。但 是, 当视频帧率减小时, 视频在播放时会有时间上的不连贯性, 并且帧率越小, 不连 贯性越明显, 压缩质量越差。考虑到帧率的影响, 视频编码压缩质量具体可以根据以 下公式计算:
MOS —VDC ps≥2A
VMOS = 1000
(MOS - VDC l + a5 - TCC -b5 -TCC - log fps < 24 当帧率大于等于 24时, 将视频质量评价参数的最大值与视频编码压缩失真的差 值作为视频编码压缩质量; 当帧率 fps小于 24时, 视频播放开始出现不连贯性, 因 此压缩质量会有一定的下降,此时,基于时间复杂度修正视频质量评价参数的最大值 与视频编码压缩失真的差值, 将修正后的结果作为视频编码压缩质量。 其中, a5和 b5为常数, 帧率越小或时间复杂度越大, 压缩质量下降越多。 在某些应用场景下, 比 如当终端设备 (网络设备, 测试设备)的运算能力太低时, 本节涉及的各公式具体的运
, ( 1000
log
算结果也可通过查表替代, 例如 、 fpS )。 该视频编码压缩质量即可衡量该视频的 质]
本发明实施例无需获取完整的原始参考视频及完整的终端视频,也无需对视频流 进行完全深层的解析, 只需获取视频流的码率和帧率信息即可获得视频编码压缩质 量, 完成视频质量的评估, 评估复杂度低, 因此也可实现实时评估; 而且, 该方法考 虑了帧率以及视频内容特性中的时间复杂度的影响,更加符合人眼视觉系统对于编码 压缩失真的感知。
参见图 5, 为本发明一种获得视频编码压缩质量的方法的第三实施例流程图。 本实施例仍以应用于传输视频流的网络侧,或应用于接收视频流的接收端为例进 行说明。本实施例与上实施例的区别在于, 在上实施例中, 所获得的视频编码压缩质 量仅仅考虑了视频内容复杂度中时间复杂度的影响,在本实施例中还进一步考虑了视 频内容复杂度的另一特性即空间复杂度的影响, 该方法可以包括:
步骤 501, 获取预定时间段内视频流的帧类型、 帧大小、 帧率、 码率、 修正的码 率及时间复杂度。
本步骤中可以通过视频帧的大小或解析码流获得该视频流中的 I帧、 P帧, 并进 一步获得 I帧、 P帧的大小。 该步骤中帧率 fps、 码率 BR、 修正的帧率 MBR以及时 间复杂度 TCC的获得与前述实施例中的步骤 201 204类似, 此处不再赘述。
步骤 502, 根据码率及 P帧大小的比值确定空间复杂度。
通过对大量码流数据的统计分析实验, 在一定码率下, 空间复杂度大的序列一般 比空间复杂度小的序列的平均 I帧大些, P/B帧小一些, 因此编码码率 Br与平均 P 帧大小的比值在一定程度上可以反映视频的内容特性即空间复杂度,该空间复杂度记 为 SCC。
该确定空间复杂度的方法具体可以包括以下步骤 601 602:
步骤 601, 根据 P帧大小确定预定时间段内的平均 P帧大小。
该步骤中计算平均 P帧的大小与前述实施例中步骤 401计算平均 I帧的大小的方 法类似, 此处不再赘述。 将平均 P帧大小记为 ABP。
步骤 602, 根据码率与平均 P帧大小的比值确定空间复杂度。 算:
Figure imgf000014_0001
其中, bo为常数。
步骤 503, 根据修正的码率, 时间、 空间复杂度, 以及视频质量评价参数计算视 频编码压缩失真。
时间复杂度或空间复杂度或时间复杂度及空间复杂度大的视频,在同一码率下的 压缩失真越大。 视频编码压缩失真的计算可以依据以下公式:
Figure imgf000014_0002
VDc为视频编码压缩失真, M0S为视频质量评价参数, 其中, MOSmax为视频质 量评价参数的最大值, 代表视频的最高分 (如评分为五分制, 则为 5), MOSmm为视 频质量评价参数的最小值, 代表视频的最低分 (如评分为五分制, 则为 1), Cl di, ei c2 d2和 e2为常数。
步骤 504, 根据视频编码压缩失真以及帧率计算视频编码压缩质量。
在获得视频编码压缩失真后,即可采用与前述实施例中的步骤 206中相同的公式 计算获得视频编码压缩质量。
本发明实施例获取视频流的码率和帧率信息即可获得视频编码压缩质量,完成视 频质量的评估, 评估复杂度低, 因此也可实现实时评估; 而且, 该方法考虑了帧率以 及视频内容特性的时间、空间复杂度的影响, 更加符合人眼视觉系统对于编码压缩失 真的感知。
在本发明的另一实施例中,在获得视频编码压缩失真时也可以只考虑空间复杂度 SCC的影响, 而不考虑空间复杂度 TCC, 此时, 视频编码压缩失真的计算可以依据 以下公式:
Figure imgf000014_0003
fi, f2 f3禾 P f4为常数。
考虑到帧率的影响,其对应的视频编码压缩质』 :具体可以采用与前述实施例中的 步骤 206中相同的公式计算获得视频编码压缩质量
参见图 7, 为本发明一种获得视频编码压缩质 j :的方法的第四实施例流程图。 本实施例仍以应用于传输视频流的网络侧,或应用于接收视频流的接收端为例进 行说明。本实施例与上实施例的区别在于,在本实施例中获得视频内容复杂度也即时 间、 空间复杂度的方法与前述实施例不同。 该方法可以包括:
步骤 701, 获取预定时间段内视频流的帧类型、 帧率、 码率、 修正的码率及视频 帧量化参数。
本步骤中可以通过视频帧的大小或解析码流获得该视频流中的 I帧、 P帧, 并进 一步获得 I帧、 P帧的大小。 该步骤中帧率 fps、 码率 BR、 修正的帧率 MBR的获得 与前述实施例中的步骤 201 203类似, 此处不再赘述。
本步骤中, 还需要获得视频流中视频帧的量化参数, 记为 QP。 量化参数 (QP)是 编码过程的一个重要参数,这个参数的设定决定了视频图像的编码质量, QP越大时, 视频图像质量越差。 具体的 QP值可通过解析视频流获得。
步骤 702, 计算时间复杂度。
在某一 QP下, P帧越大表明视频的时间复杂度越大, P帧的平均每个像素的比 特数 (记为 ABPP) 能够反映时间复杂度的大小, 该确定时间复杂度可以包括: 根据视频帧类型计算视频帧量化参数下 P帧的每个像素的比特数;
根据 P帧的每个像素的比特数以及视频帧量化参数对应的第一参量,计算时间复 杂度。
具体的, 时间复杂度可以依据以下公式计算:
TCC = h ABPP + h2
其中, !^和!^是与 QP相关的第一参数, 即每一个 QP值对应一组!^和!^。 该视频流时间复杂度的计算也可以通过两种方式但不仅限于该两种方式获得,一 是根据每个 P帧的 QP和 ABPP计算得到一个 TCC,然后通过平均值计算的方法得到 该段视频流的 TCC;二是统计该段视频流的各个 P帧的 QP的平均值和 ABPP的平均 值, 然后通过上式计算得到该段视频流的 TCC。 具体单帧的时间复杂度计算详见申 请号为 200910161628.9,公告号为 CN101635846B,名称为 "一种视频质量评估方法、 系统及装置" 的专利的描述。
步骤 703, 计算空间复杂度。
在某一 QP下, I帧越大表明视频的空间复杂度越大, I帧的平均每个像素的比特 数 (ABIP) 能够反映空间复杂度的大小, 该计算空间复杂度的过程可以包括:
根据视频帧类型计算视频帧量化参数下 I帧的每个像素的比特数;
根据 I帧的每个像素的比特数以及视频帧量化参数对应的第二参量, 计算空间复 杂度。
具体的, 空间复杂度可以依据以下公式计算:
SCC = jl - ABIP+ j2
其中, ^和』2是与 QP相关的第二参数, 即每一个 QP值对应一组 ^和』2
同理,该视频流的空间复杂度的计算也可以通过两种方式但不仅限于该两种方式 获得, 一是根据每个 I帧的 QP和 ABIP计算得到一个 SCC, 然后通过平均值计算的 方法得到该段视频流的 SCC; 二是统计该段视频流各个 I帧的 QP的平均值和 ABIP 的平均值, 然后通过上式计算得到该段视频流的 SCC。 具体单帧的时间复杂度计算 详见申请号为 200910161628.9, 公告号为 CN101635846B, 名称为 "一种视频质量评 估方法、 系统及装置" 的专利的描述。
步骤 702、 703的顺序可以调换, 也可以同时进行。
步骤 704, 根据修正的码率, 时间、 空间复杂度, 以及视频质量评价参数计算视 频编码压缩失真。
步骤 705, 根据视频编码压缩失真以及帧率计算视频编码压缩质量。
在确定 TCC、 SCC后, 步骤 704、 705中对视频编码压缩失真以及视频编码压缩 质量的计算可以参照前述实施例中步骤 503 504的方法获得。
在另一实施例中,该视频编码压缩失真以及视频编码压缩质量的计算也可以仅仅 以及 TCC或 SCC进行计算, 具体过程请参照前述实施例中的相应描述, 此处不再赘 述。
本发明实施例降低了评估复杂度, 因此可实现实时评估; 而且, 该方法考虑了帧 率以及视频内容特性的时间、空间复杂度的影响, 更加符合人眼视觉系统对于编码压 缩失真的感知。
参见图 8, 为本发明一种获得视频编码压缩质量的方法的第五实施例流程图。 本实施例仍以应用于传输视频流的网络侧,或应用于接收视频流的接收端为例进 行说明。 该方法可以包括:
步骤 801, 获取预定时间段内视频流的帧类型及视频帧量化参数。
本步骤中可以通过视频帧的大小或解析码流获得该视频流中的 I帧、 P帧, 并获 得视频流中视频帧的量化参数 QP。
步骤 802, 根据视频流的平均视频帧量化参数计算视频流的视频编码压缩基本失 真。
由于人眼的视觉掩盖, 在一定 QP下, 时间复杂度和空间复杂度大的视频压缩失 真会相对小些。 本步骤中, 可先根据 QP得到其量化步长 (QPstep), 再由 QPstep通 过查表或者公式计算得出视频编码压缩基本失真 ^, 具体可以通过以下公式获得:
VDc'= (MOSmax _MOU/ cl(^)或者
VDC ' = (MOSmax - MOSmm ) ·
Figure imgf000017_0001
其中, /M"cl^P)是与 QP成正比的函数, 是与 QPstep成正比的 函数, 且均在 0 到 1 之间, 其形式可以是线性也可以是非线性的, 比如可以是 func (QP、 =
Figure imgf000017_0002
+ k2 ' QP。 步骤 803, 根据视频帧的量化参数下 P帧的平均每个像素的比特数计算时间复杂 度; 根据视频帧的量化参数下 I帧的平均每个像素的比特数计算空间复杂度。
该步骤与前述实施例中步骤 702 703 相同, 此处不再赘述。 在获得时间复杂度
TCC以及空间复杂度 SCC后, 即可执行下一步骤 804。
步骤 804, 根据时间复杂度和空间复杂度修正视频编码压缩基本失真, 计算视频 编码压缩失真。 该修正过程可以采用基于时间复杂度和空间复杂度的函数"^^ 71^'^^), 来 对视频编码压缩基本失真进行修正。 具体可以采用以下公式:
VDc = VDc y-func2(TCC, SCC) 其中, fwjCi {TCC,scc")是与 和 scc成反比的函数,且在 0到 1之间, TCC 和 /或 SCC越大, ^^(^^'^^)越小, 其形式可以是线性也可以是非线性的, 比 如可以是/ c2(7UC, SCC) = k3 . TCC + k4 . SCC + k5 步骤 805, 根据视频编码压缩失真以及帧率计算视频编码压缩质量。
在确定 TCC、 SCC、 VDc后, 视频编码压缩质量的计算可以参照前述实施例中 步骤 504的方法获得。
本发明实施例获取视频流的码率和帧率信息即可获得视频编码压缩质量,完成视 频质量的评估, 评估复杂度低, 因此也可实现实时评估; 而且, 该方法考虑了帧率以 及视频内容特性的时间、空间复杂度的影响, 更加符合人眼视觉系统对于编码压缩失 真的感知。
在本发明的另一实施例中,在获得视频编码压缩质量时也可以只考虑空间复杂度 SCC或时间复杂度 TCC, 也即只采用空间复杂度的函数来修正视频编码压缩基本失 真, 或只采用时间复杂度的函数来修正视频编码压缩基本失真,进而在获得视频编码 压缩失真后, 确定视频编码压缩质量。
以上各实施例中的步骤顺序可以根据需要调整, 并非局限于上述步骤顺序。 以上各方法实施例可以应用于传输视频流的网络侧,或应用于接收视频流的接收 端进行视频质量评估。
以上各方法实施例也还可以应用于视频流的发送端,与应用在上述网络侧和接收 端的区别仅在于,在发送端所获得的视频流信息中, 由于不存在视频数据包或视频帧 丢失的情况,所以视频流总数据量就等于待发送的视频数据包净载的总数据量或视频 帧的总数据量。
本领域的技术人员可以清楚地了解到本发明实施例中的技术可借助软件加必需 的通用硬件平台的方式来实现。基于这样的理解,本发明实施例中的技术方案本质上 或者说对现有技术做出贡献的部分可以以软件产品的形式体现出来,该计算机软件产 品可以存储在存储介质中, 如 ROM/RAM、磁碟、光盘等, 包括若干指令用以使得一 台计算机设备(可以是个人计算机, 服务器, 或者网络设备等)执行本发明各个实施 例或者实施例的某些部分所述的方法。
以上是对本发明方法实施例的描述, 下面对实现上述方法的装置进行介绍。 参见图 9, 为本发明一种获得视频编码压缩质量的装置的第一实施例框图。 该装置可以包括:
信息获取单元 901, 用于获取视频流信息, 所述视频流信息包括视频帧类型、 视 频帧大小、 帧率和码率;
复杂度计算单元 902, 用于根据所述信息获取单元 901获取的视频流信息计算视 频内容复杂度,所述视频内容复杂度包括时间复杂度或空间复杂度或时间复杂度及空 间复杂度;
质量评估单元 903, 用于根据所述信息获取单元 901获取的码率、 所述帧率和所 述复杂度计算单元 902获得的视频内容复杂度计算视频编码压缩质量。
信息获取单元 901首先获得视频流信息, 该信息可以包括视频帧类型及大小、帧 率和码率, 当然也还可以包括其他信息, 例如视频帧量化参数等, 复杂度计算单元 902根据视频流信息确定视频内容复杂度, 该视频内容复杂度可以包括时间复杂度或 空间复杂度或时间复杂度及空间复杂度,在计算时间复杂度时, 具体可以根据视频帧 中的 I帧大小以及上步骤获得码率确定, 也可以当视频流信息中还包括视频帧量化参 数信息时,根据该量化参数对应的 P帧的每个像素对应的比特数确定;在计算空间复 杂度时,具体可以根据视频帧中的 P帧大小以及码率确定, 也可以当视频流信息中还 包括视频帧量化参数信息时,根据该量化参数对应的 I帧的每个像素对应的比特数确 定。最后, 质量评估单元 903可以根据码率、帧率及视频内容复杂度来确定视频编码 压缩质量; 也可以首先根据码率和视频内容复杂度确定视频编码压缩失真,然后根据 该视频编码压缩失真及帧率确定视频编码的压缩质量。
本发明实施例通过上述单元获得了视频编码压缩质量,该装置既不需要获得整个 原始参考视频以及终端视频,也不需要深层解析视频码流的具体 MV或残差值,大大 减小了视频质量评估的复杂度, 能够实时进行评估。 同时, 由于考虑了视频内容特性 (即视频内容复杂度)和帧率的影响, 使评估出的编码压缩质量更符合人眼的主观感 受。
参见图 10, 为本发明一种视频编码压缩质量评估装置的第二实施例框图。 本实施例中, 该装置除了可以包括信息获取单元 1001, 复杂度计算单元 1002, 质量评估单元 1003之外, 还可以包括码率修正单元 1004。
本实施例中, 信息获取单元 1001可以包括: 码率获取子单元用于获取预定时间 段内的视频流总数据量;并根据所述视频流总数据量与所述预定时间段的比值确定码 率。
复杂度计算单元 1002可以包括:
第一时间子单元 1021, 用于当当所述视频内容复杂度包括时间复杂度时, 根据 所述信息获取单元获取的所述视频帧类型及大小计算所述预定时间段内的平均 I帧大 小; 并根据所述码率与所述平均 I帧的大小的比值确定所述时间复杂度;
第一空间子单元 1022, 用于当所述视频内容复杂度包括空间复杂度时, 根据所 述信息获取单元获取的所述视频帧类型及大小计算所述预定时间段内的平均 P 帧大 小; 并根据所述码率与所述平均 P帧的大小的比值确定所述空间复杂度。
码率修正单元 1004, 用于在所述质量评估单元 1003根据所述码率、 所述帧率及 所述视频内容复杂度确定视频编码压缩质量之前,根据所述码率及所述帧率计算修正 的码率; 码率修正单元 1004可以进一步包括:
比较子单元 1041, 用于确定所述信息获取单元 1001获取的所述帧率与参考帧率 之间的较小值; 计算子单元 1042, 用于根据所述码率与所述较小值的比值确定所述修正的码率。 质量评估单元 1003, 具体用于根据所述码率修正单元 1004获取的修正的码率, 所述帧率及所述视频内容复杂度确定视频编码压缩质量。 该质量评估单元 1003可以 包括:
失真计算子单元 1031, 用于根据所述码率修正单元获得的修正的码率,所述视频 内容复杂度, 以及视频质量评价参数确定视频编码压缩失真;
评估子单元 1032, 用于根据所述视频编码压缩失真以及所述帧率确定所述视频 编码压缩质量。 评估子单元 1032, 具体用于当所述帧率大于等于 24时, 将所述视频 质量评价参数的最大值与所述视频编码压缩失真的差值作为所述视频编码压缩质量; 当所述帧率小于等于 24时, 基于所述视频内容复杂度修正所述视频质量评价参数的 最大值与所述视频编码压缩失真的差值, 将修正后的结果作为所述视频编码压缩质 在本发明的另一实施例中,若信息获取单元获取的视频流信息还包括视频帧量化 参数, 则该复杂度计算单元可以包括:
第二时间子单元,用于当所述信息获取单元获取的视频流信息还包括视频帧量化 参数, 且所述视频内容复杂度包括时间复杂度时,根据所述视频帧类型计算所述视频 帧量化参数下 P帧的每个像素的比特数;并根据所述 P帧的每个像素的比特数以及所 述视频帧量化参数对应的第一参量, 计算所述时间复杂度;
第二空间子单元,用于当所述信息获取单元获取的视频流信息还包括视频帧量化 参数, 且所述视频内容复杂度包括空间复杂度时,根据所述视频帧类型计算所述视频 帧量化参数下 I帧的每个像素的比特数; 并根据所述 I帧的每个像素的比特数以及所 述视频帧量化参数对应的第二参量, 计算所述空间复杂度。
在通过上述复杂度计算单元获得视频内容复杂度后,也可以通过上述码率修正单 元 1004和质量评估单元 1003获得视频编码质量。
本发明实施例通过上述单元获得了视频编码压缩质量,该装置既不需要获得整个 原始参考视频以及终端视频,也不需要深层解析视频码流的具体 MV或残差值,大大 减小了视频质量评估的复杂度, 能够实时进行评估。 同时, 由于考虑了视频内容特性 (即视频内容复杂度)和帧率的影响, 使评估出的编码压缩质量更符合人眼的主观感 受。
参见图 11, 为本发明一种终端的第一实施例框图。
本实施例中, 该终端可以包括第一收发装置 1101及第一处理器 1102。 第一收发装置 1101, 用于接收视频流。
第一处理器 1102, 用于在所述第一收发装置 1101接收到的视频流中获取视频流 信息, 所述视频流信息包括视频帧类型、 视频帧大小、 帧率和码率; 根据所述视频流 信息计算视频内容复杂度,所述视频内容复杂度包括时间复杂度或空间复杂度或时间 复杂度及空间复杂度; 根据所述码率、所述帧率和所述视频内容复杂度计算视频编码 压缩质量。
本实施例中, 该终端可以设置在视频流的接收端, 获得视频编码压缩质量, 该终 端大大减小了视频质量评估的复杂度, 能够实时进行评估。 同时, 由于考虑了视频内 容特性(即视频内容复杂度)和帧率的影响, 使评估出的编码压缩质量更符合人眼的 主观感受。
参见图 12, 为本发明一种终端的第二实施例框图。
本实施例中, 该终端可以包括第二收发装置 1201及第二处理器 1202。
第二收发装置 1201, 用于发送视频流。
第二处理器 1202, 用于在所述第二收发装置 1201发送的视频流中获取视频流信 息, 所述视频流信息包括视频帧类型、 视频帧大小、 帧率和码率; 根据所述视频流信 息计算视频内容复杂度,所述视频内容复杂度包括时间复杂度或空间复杂度或时间复 杂度及空间复杂度; 根据所述码率、所述帧率和所述视频内容复杂度计算视频编码压 缩质量。
本实施例中, 该终端可以设置在视频流的发送端, 从而获得视频编码压缩质量以 供在后续的视频质量评估中使用, 该终端大大减小了视频质量评估的复杂度, 能够实 时进行评估。 同时, 由于考虑了视频内容特性 (即视频内容复杂度) 和帧率的影响, 使评估出的编码压缩质量更符合人眼的主观感受。
参见图 13, 为本发明一种服务器的实施例框图。
该服务器位于网络侧, 可以包括第三收发装置 1301及第三处理器 1302。
第三收发装置 1301, 用于将视频流从发送端传输至接收端。
第三处理器 1302, 用于在所述第三收发装置 1301传输的视频流中获取视频流信 息, 所述视频流信息包括视频帧类型、 视频帧大小、 帧率和码率; 根据所述视频流信 息计算视频内容复杂度,所述视频内容复杂度包括时间复杂度或空间复杂度或时间复 杂度及空间复杂度; 根据所述码率、所述帧率和所述视频内容复杂度计算视频编码压 缩质量。
本实施例中, 该服务器可以设置在网络侧用于视频流的传输, 已使服务器获得视 频编码压缩质量以供在后续的视频质量评估中使用,大大减小了视频质量评估的复杂 度, 能够实时进行评估。 同时, 由于考虑了视频内容特性(即视频内容复杂度)和帧 率的影响, 使评估出的编码压缩质量更符合人眼的主观感受。
本说明书中的各个实施例均采用递进的方式描述,各个实施例之间相同相似的部 分互相参见即可, 每个实施例重点说明的都是与其他实施例的不同之处。尤其, 对于 系统实施例而言, 由于其基本相似于方法实施例, 所以描述的比较简单, 相关之处参 见方法实施例的部分说明即可。
以上所述的本发明实施方式, 并不构成对本发明保护范围的限定。任何在本发明 的精神和原则之内所作的修改、等同替换和改进等,均应包含在本发明的保护范围之 内。

Claims

权 利 要 求
1、 一种获得视频编码压缩质量的方法, 其特征在于, 包括:
获取视频流信息, 所述视频流信息包括视频帧类型、 视频帧大小、 帧率和码 根据所述视频流信息计算视频内容复杂度,所述视频内容复杂度包括时间复 杂度或空间复杂度或时间复杂度及空间复杂度;
根据所述码率、 所述帧率和所述视频内容复杂度计算视频编码压缩质量。
2、 根据权利要求 1所述的方法, 其特征在于, 所述获取视频流信息, 包括: 获取所述的视频帧类型、 视频帧大小和帧率; 以及
获取预定时间段内的视频流总数据量;
根据所述视频流总数据量与所述预定时间段的比值确定码率。
3、 根据权利要求 2所述的方法, 其特征在于, 所述视频流总数据量为接收 到的视频流数据量与丢失的视频流数据量之和。
4、 根据权利要求 1至 3中任意一项所述的方法, 其特征在于,
当所述视频内容复杂度包括时间复杂度时,根据所述视频流信息计算视频内 容复杂度包括:
根据所述视频帧类型及大小计算所述预定时间段内的平均 I帧大小; 根据所述码率与所述平均 I帧的大小的比值确定所述时间复杂度; 和 /或 当所述视频内容复杂度包括空间复杂度时,所述根据所述视频流信息计算视 频内容复杂度包括:
根据所述视频帧类型及大小计算所述预定时间段内的平均 P帧大小; 根据所述码率与所述平均 P帧的大小的比值确定所述空间复杂度。
5、 根据权利要求 4所述的方法, 其特征在于, 所述时间复杂度具体为:
Figure imgf000023_0001
其中, TCC为时间复杂度, BR为码率, ABI为平均 I帧大小, a。为常数。
6、 根据权利要求 1至 3中任意一项所述的方法, 其特征在于, 所述视频流 信息还包括视频帧量化参数;
当所述视频内容复杂度包括时间复杂度时,所述根据所述视频流信息计算视 频内容复杂度包括:
根据所述视频帧类型计算所述视频帧量化参数下 P帧的每个像素的比特数; 根据所述 P 帧的每个像素的比特数以及所述视频帧量化参数对应的第一参 量, 计算所述时间复杂度;
当所述视频内容复杂度包括空间复杂度时,所述根据所述视频流信息计算视 频内容复杂度包括:
根据所述视频帧类型计算所述视频帧量化参数下 I帧的每个像素的比特数; 根据所述 I 帧的每个像素的比特数以及所述视频帧量化参数对应的第二参 量, 计算所述空间复杂度。
7、 根据权利要求 1至 6中任意一项所述的方法, 其特征在于, 在所述根据 所述码率、所述帧率及所述视频内容复杂度计算视频编码压缩质量之前,还包括: 根据所述码率及所述帧率计算修正的码率;
所述根据所述码率、 所述帧率及所述视频内容复杂度计算视频编码压缩质 量, 包括:
根据所述修正的码率、所述帧率及所述视频内容复杂度计算视频编码压缩质
8、 根据权利要求 7所述的方法, 其特征在于, 所述根据所述码率及所述帧 率计算修正的码率, 包括:
确定获取的所述帧率与参考帧率之间的较小值;
根据所述码率与所述较小值的比值确定所述修正的码率。
9、 根据权利要求 8所述的方法, 其特征在于, 所述修正的码率具体为:
MBR =——― 30
Min(fps,30)
其中, MBR为修正的码率, BR为码率, fps为帧率, 30为所述参考帧率。
10、 根据权利要求 7至 9中任意一项所述的方法, 其特征在于, 所述根据所 述修正的码率、 所述帧率及所述视频内容复杂度计算视频编码压缩质量, 包括: 根据所述修正的码率,所述视频内容复杂度, 以及视频质量评价参数计算视 频编码压缩失真;
根据所述视频编码压缩失真以及所述帧率计算所述视频编码压缩质量。
11、 根据权利要求 10所述的方法, 其特征在于, 当所述视频内容复杂度只 包含时间复杂度时, 所述视频编码压缩失真具体为:
Figure imgf000024_0001
其中, VDc为视频编码压缩失真, MOS为视频质量评价参数, MOSmax为 视频质量评价参数的最大值, MOSmm为视频质量评价参数的最小值, MBR为 修正的码率, TCC为时间复杂度, ai, a2, a3, a4为常数。
12、 根据权利要求 10或 11所述的方法, 其特征在于, 所述根据所述视频编 码压缩失真以及所述帧率计算所述视频编码压缩质量, 包括:
当所述帧率大于等于 24时, 将所述视频质量评价参数的最大值与所述视频 编码压缩失真的差值作为所述视频编码压缩质量;
当所述帧率小于等于 24时, 基于所述视频内容复杂度及所述帧率修正所述 视频质量评价参数的最大值与所述视频编码压缩失真的差值,将修正后的结果作 为所述视频编码压缩质量。
13、 根据权利要求 12所述的方法, 其特征在于, 所述视频编码压缩质量具 体为:
MOS —VDC fps≥24
VMOS, 1000
(應匪 - C ) \ + a5 - TCC -b5 -TCC - log fps < 24 fps
14、 一种获得视频编码压缩质量的装置, 其特征在于, 包括:
信息获取单元, 用于获取视频流信息, 所述视频流信息包括视频帧类型、 视 频帧大小、 帧率和码率;
复杂度计算单元,用于根据所述信息获取单元获取的视频流信息计算视频内 容复杂度,所述视频内容复杂度包括时间复杂度或空间复杂度或时间复杂度及空 间复杂度;
质量评估单元, 用于根据所述信息获取单元获取的码率、所述帧率和所述复 杂度计算单元获得的视频内容复杂度计算视频编码压缩质量。
15、 根据权利要求 14所述的装置, 其特征在于, 所述信息获取单元包括: 码率获取子单元, 用于获取预定时间段内的视频流总数据量; 并根据所述视 频流总数据量与所述预定时间段的比值确定码率。
16、 根据权利要求 14或 15所述的装置, 其特征在于, 所述复杂度计算单元 包括:
第一时间子单元, 用于当所述视频内容复杂度包括时间复杂度时, 根据所述 信息获取单元获取的所述视频帧类型及大小计算所述预定时间段内的平均 I帧大 小; 并根据所述码率与所述平均 I帧的大小的比值确定所述时间复杂度;和 /或第 一空间子单元, 用于当所述视频内容复杂度包括空间复杂度时, 根据所述信息获 取单元获取的所述视频帧类型及大小计算所述预定时间段内的平均 P帧大小;并 根据所述码率与所述平均 P帧的大小的比值确定所述空间复杂度。
17、 根据权利要求 14或 15所述的装置, 其特征在于, 所述复杂度计算单元 包括:
第二时间子单元,用于当所述信息获取单元获取的视频流信息还包括视频帧 量化参数, 且所述视频内容复杂度包括时间复杂度时, 根据所述视频帧类型计算 所述视频帧量化参数下 P帧的每个像素的比特数;并根据所述 P帧的每个像素的 比特数以及所述视频帧量化参数对应的第一参量, 计算所述时间复杂度;
第二空间子单元,用于当所述信息获取单元获取的视频流信息还包括视频帧 量化参数, 且所述视频内容复杂度包括空间复杂度时, 根据所述视频帧类型计算 所述视频帧量化参数下 I帧的每个像素的比特数; 并根据所述 I帧的每个像素的 比特数以及所述视频帧量化参数对应的第二参量, 计算所述空间复杂度。
18、 根据权利要求 14至 17中任意一项所述的装置, 其特征在于, 还包括: 码率修正单元, 用于在所述质量评估单元根据所述码率、所述帧率及所述视 频内容复杂度确定视频编码压缩质量之前,根据所述码率及所述帧率计算修正的 码率;
所述质量评估单元, 具体用于根据所述码率修正单元获取的修正的码率、所 述帧率及所述视频内容复杂度计算视频编码压缩质量。
19、 根据权利要求 18所述的装置, 其特征在于, 所述码率修正单元包括: 比较子单元,用于确定所述信息获取单元获取的所述帧率与参考帧率之间的 较小值;
计算子单元, 用于根据所述码率与所述较小值的比值确定所述修正的码率。
20、 根据权利要求 18或 19所述的装置, 其特征在于, 所述质量评估单元包 括:
失真计算子单元, 用于根据所述码率修正单元获得的修正的码率,所述视频 内容复杂度, 以及视频质量评价参数计算视频编码压缩失真;
评估子单元,用于根据所述视频编码压缩失真以及所述帧率计算所述视频编 码压缩质量。
21、 根据权利要求 20所述的装置, 其特征在于,
所述评估子单元, 具体用于当所述帧率大于等于 24时, 将所述视频质量评 价参数的最大值与所述视频编码压缩失真的差值作为所述视频编码压缩质量;当 所述帧率小于等于 24时, 基于所述视频内容复杂度修正所述视频质量评价参数 的最大值与所述视频编码压缩失真的差值,将修正后的结果作为所述视频编码压 缩质量。
22、 一种终端, 其特征在于, 包括第一收发装置及第一处理器, 所述第一收发装置, 用于接收视频流;
所述第一处理器,用于在所述第一收发装置接收到的视频流中获取视频流信 息, 所述视频流信息包括视频帧类型、 视频帧大小、 帧率和码率; 根据所述视频 流信息计算视频内容复杂度,所述视频内容复杂度包括时间复杂度或空间复杂度 或时间复杂度及空间复杂度; 根据所述码率、所述帧率和所述视频内容复杂度计 算视频编码压缩质量。
23、 一种终端, 其特征在于, 包括第二收发装置及第二处理器, 所述第二收发装置, 用于发送视频流;
所述第二处理器, 用于在所述第二收发装置发送的视频流中获取视频流信 息, 所述视频流信息包括视频帧类型、 视频帧大小、 帧率和码率; 根据所述视频 流信息计算视频内容复杂度,所述视频内容复杂度包括时间复杂度或空间复杂度 或时间复杂度及空间复杂度; 根据所述码率、所述帧率和所述视频内容复杂度计 算视频编码压缩质量。
24、 一种服务器, 其特征在于, 位于网络侧, 所述服务器包括第三收发装置 及第三处理器,
所述第三收发装置, 用于将视频流从发送端传输至接收端;
所述第三处理器, 用于在所述第三收发装置传输的视频流中获取视频流信 息, 所述视频流信息包括视频帧类型、 视频帧大小、 帧率和码率; 根据所述视频 流信息计算视频内容复杂度,所述视频内容复杂度包括时间复杂度或空间复杂度 或时间复杂度及空间复杂度; 根据所述码率、所述帧率和所述视频内容复杂度计 算视频编码压缩质量。
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