43 results about "Subjective video quality" patented technology

A decoding arrangement for decoding pictures in an incoming video stream includes a noise generator for adding a dither signal containing random noise to the pictures after video decoding, to improve the subjective video quality. The noise generator adds noise to each pixel in an amount correlated to the luminance of at least a portion of the current picture.

This invention provides one visual quality evaluation method, which determines visual sequence quality according to sequence adjacent pre-set area picture element changes. This invention fully considers the visual sequence adjacent frame image content changes, especially to the time changes in motion area picture elements to fully reflect visual quality factor through adjacent frame plus front frame motion area picture for reference.

A feature amount extracting unit extracts a block distortion degree of an evaluated video y relative to an original video x, a PSNR overall temporal fluctuation degree, and a PSNR local temporal fluctuation degree as feature amounts. A weighted sum calculating unit calculates a weighted sum of these feature amounts, and calculates an objective video quality index. Frame rate detecting unit detects frame rate of the evaluated video y. A correcting unit corrects the objective video quality index based on the frame rate detected by the frame rate detecting unit. An objective evaluation index-subjective video quality mapping unit applies the corrected objective video quality index Qobj to a correlation between an objective video quality index and a subjective video quality given in advance, thereby deriving a subjective video quality estimated value DMOS.

A method for measuring video quality includes: receiving subjective video quality measuring data from a plurality of video quality measurers; photographing or capturing a test-target video image and receiving image data; calculating video quality measurement factor values with respect to the received image data, item by item; reflecting the video quality measurement factor values to the subjective video quality measuring data through video quality modeling; mapping results of the reflecting into scores; weighting the video quality measurement factor values according to their correlations with the subjective video quality measuring data; and outputting objective video quality measuring data on a screen. An associated video quality measuring system includes: a subjective video quality measurement input; an objective video quality measuring; a video quality modeling; and a video quality measuring algorithm unit.

The invention relates to a device for estimating the quality of experience (QoE) for an internet protocol television (IPTV) user, comprising a network transmission detection module, a video coding detection module and a comprehensive analysis module, wherein the network transmission detection module is connected with the comprehensive analysis module by the video coding detection module and provided with a video streaming input end. The invention also provides a method for estimating the QoE for an IPTV user, which is realized based on the device. In the method, after the network transmission detection module acquires video streaming, the network transmission detection module detects the video streaming to acquire network transmission influence parameters; then the video coding detection module detects the video streaming to acquire video coding influence parameters; and finally the comprehensive analysis module calculates the sensory mean opinion score (MOS) of the user in accordance with the network transmission influence parameters and the video coding influence parameters so as to realize the estimation for subjective video quality. The device and method provided by the invention can be used to effectively improve the QoE of the existing IPTV.

In estimating subjective video quality corresponding to main parameters (121 / 221) which are input as an input coding bit rate (121B / 221B) representing the number of coding bit rates per unit time and an input frame rate (121A / 221A) representing the number of frames per unit time of an audiovisual medium, an estimation model specifying unit specifies, on the basis of the input coding bit rate (121B / input frame rate (221A)), an estimation model (122 / 222) representing the relationship between subjective video quality and the frame rate ( / coding bit rate) of the audiovisual medium. Subjective video quality corresponding to the input frame rate (121A / input coding bit rate 221B) is estimated by using the specified estimation model (122 / 222) and output as an estimation value (123 / 223).

In estimating subjective video quality corresponding to main parameters (21) which are input as an input frame rate (21A) representing the number of frames per unit time, an input coding bit rate (21B) representing the number of coding bits per unit time, and an input packet loss rate (21C) representing a packet loss occurrence probability of an audiovisual medium, a degradation model specifying unit (12) specifies a degradation model (22) representing the relationship between the packet loss rate and the degradation in reference subjective video quality (23) on the basis of the input frame rate (21A) and input coding bit rate (21B). A desired subjective video quality estimation value (24) is calculated by correcting the reference subjective video quality on the basis of a video quality degradation ratio corresponding to the input packet loss rate (21C) calculated by using the degradation model (22).

The invention provides a video coding method, which comprises the following steps of: 1) determining video distortion D between video coded by a coding mode to be selected according to the attention degree of each macro block and original video; 2) calculating a rate distortion optimized (RDO) model according to the video distortion D; and 3) performing video coding according to the RDO model. Bythe method provided by the invention, subjective vision characteristics of a user are taken into account, and a code rate can be effectively decreased under the condition of ensuring the subjective video quality of the user.

Pre filtering is commonly used in video encoding to remove undesirable noise from video sources. Without a pre filter, the noise degrades the performance of a video encoder by wasting a number of bits to represent the noise itself, and by introducing encoding artifacts such as blocking and ringing noise. However, excess use of pre filtering will degrade subjective visual quality. This invention employs an automatic pre filter control using a subjective noise detector capable of measuring noise that strongly correlates to subjective video quality.

A decoding arrangement for decoding pictures in an incoming video stream includes a noise generator for adding a dither signal containing random noise to the pictures after video decoding, to improve the subjective video quality. The noise generator adds noise to each pixel in an amount correlated to additive noise of pixels in a prior picture, either a previously displayed picture (i.e., a previously decoded picture to which noise has been added), or a previously decoded picture.

The invention provides a method for hiding HEVC (High Efficiency Video Coding) video information. The method comprises two steps of secret information embedding and secret information extracting; during secret information embedding, a prediction model is modulated in an intra-frame prediction coding process aiming at 4*4 prediction units by analyzing an HEVC coding and decoding structure, an intra-frame coding mode is selected in a self-adapting manner by using a Lagrangian rate-distortion model to decide whether to embed secret information; a corresponding relation between two bits of information to be embedded and angle difference intervals of the prediction model, completed information embedding of the prediction model is corrected according to the two bits of information to be embedded, a prediction model of only one prediction unit in the two continuous 4*4 prediction units in most cases is required to be corrected, so that correction bits is reduced under the same hiding capacity, and influence on the video quality, which is caused by the embedded secret information is reduced; objective and subjective video quality can be well ensured, and influence on a video bitstream, which is caused by the embedded secret information is greatly reduced.

In estimating subjective video quality corresponding to main parameters (121 / 221) which are input as an input coding bit rate (121B / 221B) representing the number of coding bit rates per unit time and an input frame rate (121A / 221A) representing the number of frames per unit time of an audiovisual medium, an estimation model specifying unit specifies, on the basis of the input coding bit rate (121B / input frame rate (221A)), an estimation model (122 / 222) representing the relationship between subjective video quality and the frame rate ( / coding bit rate) of the audiovisual medium. Subjective video quality corresponding to the input frame rate (121A / input coding bit rate 221B) is estimated by using the specified estimation model (122 / 222) and output as an estimation value (123 / 223).

The invention discloses a multi-layer neural network based user QoE prediction method in a video service. Data is preprocessed by selecting characteristic parameters that influence user experience from the video service, and mapping the characteristic parameters into user QoE according to fault report or non fault report of the user; a QoE prediction model of the multi-layer neural network is established, and the neural network comprises an input layer, a first hidden layer, a second hidden layer, a third hidden layer and an output layer successively from bottom to top; the preprocessed data is input, an optimal parameter value of the model is obtained, and the established neural network model is trained; and user QoE prediction is completed; According to the invention, the data is preprocessed, important characteristic attributes are selected, different types of parameters are considered in an integrated way, the video quality predicted by the model approaches the subjective video quality experience of the user more, the user QoE can be predicted in a better way, results can be back fed timely and accurately, and a service provider and a network service provider can complete the video service as well as transmission services continuously.

The invention relates to a method and a device for carrying out subjective video quality optimization coding on a P-frame sequence. The method comprises the following steps: detecting two continuous P frames which are already coded before the current P frame, and judging whether the fluctuations of the code rates of the two continuous P frames are less than a preset threshold value; when the fluctuations of the code rates of the two continuous P frames are less than the preset threshold value, predicating the structure similarity value of the current P frame according to the structure similarity value of the previous P frame of the current P frame; calculating the sum of absolute transformed difference of the current P, and calculating the predication output code rate of the current P according to the sum of absolute transformed difference; calculating the optimal quantization step length of the current P according to the structure similarity value of the current P and the predication output code rate and converting the optimal quantization step length to the optimal quantization parameter, and coding the current P according to the optimal quantization parameter. With the adoption of the method and the device, when the P frame meets code rate fluctuation condition, the optimal quantization parameter for improving a subjective video quality can be obtained in case of no obvious increase of the code rate, thus improving the subjective video quality.

In estimating subjective video quality corresponding to main parameters (121 / 221) which are input as an input coding bit rate (121B / 221B) representing the number of coding bit rates per unit time and an input frame rate (121A / 221A) representing the number of frames per unit time of an audiovisual medium, an estimation model specifying unit specifies, on the basis of the input coding bit rate (121B / input frame rate (221A)), an estimation model (122 / 222) representing the relationship between subjective video quality and the frame rate ( / coding bit rate) of the audiovisual medium. Subjective video quality corresponding to the input frame rate (121A / input coding bit rate 221B) is estimated by using the specified estimation model (122 / 222) and output as an estimation value (123 / 223).

The invention relates to a macroblock layer rate control method based on an H264 video encoding standard. The macroblock layer rate control method comprises the following steps of: A, calculating a target bit number of a current frame by using a fluid blocking model and a linear tracing theory; B, distributing the bit number of a macroblock layer; C, predicting an average absolute error ratio of the current macroblock in the current frame; D, calculating quantization parameters of the corresponding macroblock; and E, realizing rate-distortion optimization of each macroblock in the current frame by using the parameter values obtained in the step D. The macroblock layer rate control method disclosed by the invention has the beneficial effects of enabling the generated error rate to be closer to the target error rate and improving the structural similarity of video output sequences, thereby obtaining better subjective video quality.

The invention relates to an H.264 frame layer code rate control method based on a structural similarity coefficient. The structural similarity theory is utilized for distributing the H.264 frame layer code rate. The method comprises the following steps that A, the target bit number of the remaining frame is calculated; B, the structural similarity coefficient is calculated; C, the target bit number of the current frame is determined according to the structural similarity coefficient; D, a quantization parameter is calculated; and E, rate-distortion optimization is carried out. The method is characterized in that the structural similarity coefficient is defined, and the target bit number of the frame is determined on the basis of the defined structural similarity coefficient. The H.264 frame layer code rate control method has the advantages that the code rate can be more accurately controlled, and in addition, the structural similarity of the video output sequence can be improved, so that the better subjective video quality is obtained.

A decoding arrangement for decoding pictures in an incoming video stream includes a noise generator for adding a dither signal containing random noise to the pictures after video decoding, to improve the subjective video quality. The noise generator adds noise to each pixel in an amount correlated to additive noise of pixels in a prior picture, either a previously displayed picture (i.e., a previously decoded picture to which noise has been added), or a previously decoded picture.

A decoding arrangement (10, 100, 1000) for decoding pictures in an incoming video stream includes a noise generator (16 ) for adding a dither signal containing random noise to the pictures after video decoding, to improve the subjective video quality. The noise generator adds noise to each pixel in an amount correlated to the luminance of at least a portion of the current picture.

This invention is concerned with a video quality measurement method, in particular where the video signal having: an original form; encoded form in which video signal has been encoded using a compression algorithm utilising a variable quantiser step size such that the encoded signal includes a quantiser step size parameter; and, a decoded form in which the encoded video signal has been at least in part reconverted to the original form. The method comprises the steps of: a) generating a first quality measure which is a function of said quantiser step size parameter; b) generating a second quality measure which is a function of the spatial complexity of the frames represented by the video signal in the decoded form; and, c) combining the first and second measures.

The present invention discloses a method and a device for concealing the video error codes of real-time multimedia applications based on mobile network infrastructures including 3G. The present invention can increase the quality of a subjective video, and by applying manifold error code concealment technologies, conducts error code compensation on the video slice layer. The working principle of the error code concealment technology of the present invention is based on the following concealment technologies: (1) Spacial concealment: Only based on the data obtained from the current image; (2) Temporal concealment: Only based on the data obtained from a neighboring image. The error code concealment method of the present invention collects interframe mode-encoded macroblock number information from the current decoded video segment in order to determine how error code concealment is performed when the current video segment generates errors. If the percentage of the interframe mode-encoded macroblocks in a video segment exceeds a predefined threshold, then, when a neighboring segment is lost, the temporal error code concealment technology is applied, and otherwise, both spacial and temporal concealment technologies are applied. The error code concealment technology designed by the present invention not only can be conveniently embodied but also can efficiently conceal the video error codes caused by datagram loss, transmission errors, network delays, etc. The method can be conveniently applied to various hand-held devices, such as mobile phones, PDAs, etc.

A video quality evaluation method based on 3D wavelet transform utilizes 3D wavelet transform in the video quality evaluation, for transforming the group of pictures (GOP for short) of the video. By splitting the video sequence on a time axis, time-domain information of the GOPs is described, which to a certain extent solves a problem that the video time-domain information is difficult to be described, and effectively improves accuracy of objective video quality evaluation, so as to effectively improve relativity between the objective quality evaluation result and the subjective quality judged by the human eyes. For time-domain relativity between the GOPs, the method weighs the quality of the GOPs according to the motion intensity and the brightness, in such a manner that the method is able to better meet human visual characteristics.

The invention provides a method and a device for evaluating video sequence distortion. The method for evaluating the video sequence distortion includes: as for distortion of each local region in each frame of a video sequence, obtaining a distortion sensitivity factor corresponding to the distortion by the aid of a texture intensity factor, a fixation point factor, a movement intensity factor and a distortion area factor at the position of the distortion, and taking a sum of products of the distortion of all local regions in each frame and the corresponding distortion sensitivity factors of the distortion as a distortion sum of the frame; as for each frame in the video sequence, obtaining a distortion sum corrected value of the frame according to a distortion sum of one of a plurality of frames adjacent to the frame; and obtaining a time domain weight number of the frame according to a corresponding moment of the frame in the video sequence, calculating a sum of products of distortion sum corrected values of all the frames and time domain weight numbers corresponding to the frames, and dividing a normalized numerical value so that average distortion of the video sequence is obtained. The average distortion of the video sequence obtained by the method is highly consistent with a subjective video quality evaluation result.

A decoding arrangement for decoding pictures in an incoming video stream includes a noise generator for adding a dither signal containing random noise to the pictures after video decoding, to improve the subjective video quality. The noise generator adds noise to each pixel in an amount correlated to additive noise of pixels in a prior picture, either a previously displayed picture (i.e., a previously decoded picture to which noise has been added), or a previously decoded picture.

The invention relates to a macroblock layer rate control method based on an H264 video encoding standard. The macroblock layer rate control method comprises the following steps of: A, calculating a target bit number of a current frame by using a fluid blocking model and a linear tracing theory; B, distributing the bit number of a macroblock layer; C, predicting an average absolute error ratio of the current macroblock in the current frame; D, calculating quantization parameters of the corresponding macroblock; and E, realizing rate-distortion optimization of each macroblock in the current frame by using the parameter values obtained in the step D. The macroblock layer rate control method disclosed by the invention has the beneficial effects of enabling the generated error rate to be closer to the target error rate and improving the structural similarity of video output sequences, thereby obtaining better subjective video quality.

When subjectively estimating a video quality for main parameters (121 / 221) by inputting an input encoded bit rate (121B / 221B) indicating an encoded bit quantity per unit time and an input frame rate (121A / 221A) indicating a frame quantity per unit time for a video medium, an estimation model specifying unit (112 / 212) specifies an estimation model (122 / 222) indicating the relationship between a video medium frame rate ( / encoded bit rate) and the subjective video quality according to the input encoding bit rate (121B / input frame rate (221A)), estimates the subjective video quality for the inputframe rate (121A / input encoded bit rate 221B) by using the specified estimation model (122 / 222), and outputs it as an estimated value (123 / 223).

A feature amount extracting unit extracts a block distortion degree of an evaluated video y relative to an original video x, a PSNR overall temporal fluctuation degree, and a PSNR local temporal fluctuation degree as feature amounts. A weighted sum calculating unit calculates a weighted sum of these feature amounts, and calculates an objective video quality index. Frame rate detecting unit detects frame rate of the evaluated video y. A correcting unit corrects the objective video quality index based on the frame rate detected by the frame rate detecting unit. An objective evaluation index-subjective video quality mapping unit applies the corrected objective video quality index Qobj to a correlation between an objective video quality index and a subjective video quality given in advance, thereby deriving a subjective video quality estimated value DMOS.