32results about How to "Reflect quality changes" patented technology

The invention discloses a stereo image quality objective evaluation method based on visual perception. Firstly, a stereo image is divided into a strong edge block, a weak edge block , a flat block and a texture block, and characteristic information reflecting image quality and depth perception of different zone blocks is extracted through computation so as to obtain stereo image characteristic vectors; and then the characteristic vectors of distorted stereo images of the same distortion type in a distorted stereo image set are trained through support vector regression, and each distorted stereo image of the same distortion type is tested by a support vector regression training model to obtain the objective image quality evaluation forecast value of each distorted stereo image. The method has the advantages that the obtained characteristic vector information reflecting the image quality and the depth perception has stronger stability and can better reflect the quality change condition of the stereo images, and the relevance of an objective evaluation result and subjective perception is improved.

The invention discloses a stereo image quality objective evaluation method, which comprises the following steps of: performing singular value decomposition on left and right viewpoint images of undistorted stereo images and distorted stereo images, extracting characteristic vectors of the left and right viewpoint images of the distorted stereo images, and performing linear weighting on the characteristic vectors of the left and right viewpoint images to obtain the characteristic vectors of the distorted stereo images; and training the characteristic vectors of the distorted stereo images of the same distortion type in a distorted stereo image set by using support vector regression, and testing each distorted stereo image of the same distortion type by utilizing a support vector regression training mode to obtain image quality objective evaluation predicted values of each distorted stereo image. The method has the advantages of mapping raw data into a high-dimensional characteristic space and performing linear estimation in the high-dimensional characteristic space to construct an optimal linear function so as to avoid the complex process of simulating the related characteristics and mechanism of a human vision system and improve correlation between objective evaluation results and subjective perception.

The invention discloses a no-reference objective three-dimensional image quality evaluation method based on binocular visual perception. The method comprises the steps of constructing a converging one-eyed image of a distorted three-dimensional image by using an energy gain control model, and constructing left and right disparity images and indefinite left and right images by using left and right viewpoint images; then extracting a curvelet domain feature from the converging one-eyed image, and separately extracting a generalized Gaussian fitting parameter feature and a lognormal distribution fitting parameter feature from the left and right disparity images and the indefinite left and right images, wherein the three features are used as three-dimensional image feature information; and finally, constructing a relation between three-dimensional image features and average subjective scoring differences through support vector regression to obtain an objective quality evaluation predicted value of the distorted three-dimensional image. The method has the advantages that the acquired feature vector of the distorted three-dimensional image has strong stability and can reflect the quality change condition of the distorted three-dimensional image, the objective evaluation has good consistency with subjective perception of human eyes, and the correlation between the objective evaluation result and the subjective perception is improved.

The invention discloses a reference-free three-dimensional picture quality objective evaluation method based on machine learning. The reference-free three-dimensional picture quality objective evaluation method comprises the steps that a vision dictionary list is structured in a training stage, sparse coefficient matrixes of all subblocks in a left viewpoint picture and all subblocks in a right viewpoint picture are calculated respectively for the left view point picture and the right view point picture of any distortion three-dimensional picture according to the structured vision dictionary list, the characteristic vector of the left viewpoint picture and the characteristic vector of the right viewpoint picture are obtained through the maximum pooling method, characteristic extraction is simple, and the computation complexity is low; a support vector regression training model of the left viewpoint picture and a support vector regression training model of the right viewpoint picture are structured, objective quality evaluation predictive values, corresponding to each characteristic vector in a test sample data set, of the left viewpoint picture and the right viewpoint picture respectively are obtained through prediction, weighing is conducted according to characteristic vector information, the objective quality evaluation prediction value of the three-dimensional picture is obtained, and the correlation between the objective evaluation result and subjective perception is high.

The invention discloses a visual perception-based three-dimensional image quality objective evaluation method which comprises the steps of: firstly, obtaining an objective evaluation measurement value of each pixel point through calculating a local phase characteristic and a local amplitude characteristic of each pixel point in left and right viewpoint images of a three-dimensional image, dividing the three-dimensional image into a shielding region, a binocular inhibition region and a binocular fusion region by a region detection method; and secondly, evaluating all regions respectively and fusing evaluation results to obtain a final image quality objective evaluation prediction value. The visual perception-based three-dimensional image quality objective evaluation method has the advantages that the obtained information for reflecting local phase and local amplitude characteristics has strong stability and can well reflect quality change condition of the three-dimensional image, and the image quality evaluation method of the shielding region, the binocular inhibition region and the binocular fusion region can well reflect the visual perception characteristic of the human visual system, and is effectively improved in correlation of objective evaluation result and subjective perception.

The invention discloses a stereo-image quality objective evaluation method based on a characteristic image. Parallax stereograms of an original and undistorted stereo-image and a distorted and to be evaluated stereo-image are respectively calculated, then by means of the minimum changing image which can be observed by eyes of a left eyepoint image of the distorted and to be evaluated stereo-image and a gradient of disparity image of an anaglyph between a left eyepoint image and a right eyepoint image of the original and undistorted stereo-image, a first structure similarity of the two parallax stereograms is calculated, and an objective evaluation value of the image quality of the distorted and to be evaluated stereo-image is obtained. The stereo-image quality objective evaluation method based on a characteristic image has the advantages that the obtained Parallax stereograms can well reflect the effects of different parallax on stereo-image quality, the structure similarity which is calculated and obtained according to the characteristic image can well reflect the changing conditions of stereo-image quality, the evaluation result is enabled to be more accord with a human visual system, and thereby the correlation of the objective evaluation result and the subjective perception is effectively improved.

The invention discloses a tone mapping image quality objective evaluation method based on a global characteristic, wherein the method comprises two processes of a training period and a testing period. Influences of a natural scene statistics characteristic and a color statistics characteristic to tone mapping are considered. A global characteristic vector of a tone mapping image is extracted. Then support vector regression is utilized for training the global characteristic vectors of all tone mapping images in a training image set, thereby constructing a quality predication model. In the testing period, through calculating the global characteristic vector of the tone mapping image for testing, and a quality objective evaluation predicated value of the tone mapping image is obtained through predicating according to the quality predication model which is constructed in the training period. Because the obtained global characteristic vector information has relatively high stability and furthermore can well reflect the quality change condition of the tone mapping image, correlation between an objective evaluation result and subjective perception is effectively improved.

The invention discloses a stereo image quality objective evaluation method based on a gradient structure tensor. The method comprises the following steps of: calculating the gradient structure tensor of each pixel point by calculating a horizontal gradient, a perpendicular gradient and a viewpoint gradient of each pixel point in a left viewpoint image of a stereo image, and performing matrix resolving to obtain a characteristic value and a characteristic vector of the gradient structure tensor of each pixel point; then dividing the left viewpoint image into a sensitive region and a non-sensitive region by using a region detection method; and finally obtaining a final image quality objective evaluation forecast value according to the region type of each pixel. The stereo image quality objective evaluation method has the advantages that the characteristic value and the characteristic vector of the gradient structure tensor are relatively high in stability and can well reflect the quality change of the stereo image; and furthermore, the pixel points in the sensitive region can be evaluated, so that the relativity between an objective evaluation result and subjective perception can be effectively improved.

The invention discloses a relocation image quality evaluation method. According to the method, the influences of structure distortion and content loss on relocation are considered, a similarity transformation matrix is utilized to establish a transformation relation between an original image and a relocation image, the structure distortion under multiple scales is calculated according to the similarity transformation matrix, and the content loss under multiple scales is calculated according to the area change of a quadrangular grid; then support vector regression is utilized to train feature vectors composed of the structure distortion and the content loss under multiple scales in a training set, and a support vector regression training model is constructed; and at a test stage, the feature vectors of the relocation image in a test set are calculated, and an objective qualitative evaluation prediction value of the relocation image in the test set is obtained through prediction according to the support vector regression training model. Since the obtained feature vectors have high stability and can well reflect the quality change of the relocation image, the relevancy between an objective evaluation result and subjective perception is effectively improved.

The present invention discloses a stereoscopic image quality objective evaluation method. Response output after lateral geniculate nucleus processing of each pixel in each of a left viewpoint image and a right viewpoint image of an undistorted stereoscopic image and a distorted stereoscopic image, response output after primary monocular visual cortex processing, response output on different parallax planes after primary binocular visual cortex processing of pixels at the same coordinate position in the left viewpoint image and the right viewpoint image of the distortion stereoscopic image and pixels at the same coordinate position in the left viewpoint image and the right viewpoint image of the undistorted stereoscopic image, and response output on different parallax planes after second binocular visual cortex processing of the pixels at the same coordinate position in the left viewpoint image and the right viewpoint image of the distortion stereoscopic image and the pixels at the same coordinate position in the left viewpoint image and the right viewpoint image of the undistorted stereoscopic image are calculated, so as to obtain a quality vector of the distorted stereoscopic image. Through adoption of the method, the quality change of the distorted stereoscopic image can be well reflected, and a correlation between an objective evaluation result and subjective perception is effectively improved.

The invention discloses an objective three-dimensional image quality evaluation method based on structure and texture separation. The method includes the steps that firstly, structure and texture separation is conducted on a left viewpoint image body and a right viewpoint image body of an original undistorted three-dimensional image and a left viewpoint image body and a right viewpoint image body of a distorted three-dimensional image to be evaluated to obtain structure images and texture images of the left viewpoint image bodies and structure images and texture images of the right viewpoint image bodies; gradient similarity is used for evaluating the structure images of the left viewpoint image bodies and the structure images of the right viewpoint image bodies respectively, structural similarity is used for evaluating the texture images of the left viewpoint image bodies and the texture images of the right viewpoint image bodies, and an objective image quality evaluation prediction value of the distorted three-dimensional image to be evaluated is obtained through fusion. The objective three-dimensional image quality evaluation method based on structure and texture separation has the advantages that the structure images obtained through decomposition and the texture images obtained through decomposition can well represent influences on image quality of image structure and texture information, so that it seems that an evaluation result better conforms to a human visual system, and therefore the relevance of the objective evaluation result and subjective perception is effectively improved.

The invention discloses a remote sensing image fusion quality evaluation method, which comprises the steps of extracting LBP feature statistical histograms, edge histograms and spectral features of sub-blocks in different waveband images as feature vectors, and constructing an original multivariate Gaussian model in a training stage; in the test stage, constructing original multivariate Gaussian models in the test stage, and calculating a full-resolution quality evaluation prediction value according to the two original multivariate Gaussian models constructed during training and testing; calculating spectral similarity and spatial similarity between all waveband images of the multispectral image referred by the test remote sensing fusion image and downsampling waveband images obtained after downsampling operation is carried out on all waveband images of the test remote sensing fusion image, and obtaining a resolution reduction quality evaluation prediction value; and obtaining an objective quality evaluation prediction value. Due to the fact that the obtained feature vector information can well reflect the quality change condition of the remote sensing fusion image, the correlationbetween an objective evaluation result and human eye subjective perception is effectively improved.

The invention discloses an objective evaluation method for the stereo image quality on the basis of image decomposition. The objective evaluation method for the stereo image quality on the basis of the image decomposition comprises the following steps: firstly, respectively decomposing the left viewpoint image of a distorted stereo image to be evaluated into a recovery image and an interference image; decomposing the right viewpoint image of the distorted stereo image to be evaluated into a recovery image and an interference image; respectively evaluating the recovery images of the left viewpoint image and the right viewpoint image by adopting the local phase characteristic and the local vibration amplitude characteristic; respectively evaluating the interference images of the left viewpoint image and the right viewpoint image by using a singular value vector; and obtaining the objective evaluation predicted value for the distorted stereo image quality to be evaluated. The objective evaluation method for the stereo image quality on the basis of the image decomposition has the advantages that the recovery images and the interference images obtained by decomposition can better represent the influence of an image detail and redundant information on the image quality, so that an evaluation result can better conform to the human vision system, and therefore the correlation of an objective evaluation result and subjective perception can be effectively improved.

The invention discloses a method for objectively evaluating the quality of a three-dimensional image based on three-dimensional structural similarity. The method comprises the following steps of: calculating to obtain parallax space maps of an initial undistorted three-dimensional image and a distorted three-dimensional image to be evaluated respectively, calculating to obtain the three-dimensional structural similarity between the parallax space map of the initial undistorted three-dimensional image and the parallax space map of the distorted three-dimensional image to be evaluated, and obtaining the objective evaluation predicted value of the quality of the distorted three-dimensional image to be evaluated. The method has the advantages that the obtained three-dimensional structural similarity can reflect the influence of different parallaxes on the three-dimensional image well, and only a unit with the low three-dimensional structural similarity can be evaluated, so that the objective evaluation result and the correlation of subjective perception are effectively improved.

The invention discloses a three-dimensional image quality objective assessment method based on a three-dimensional gradient amplitude. Firstly, a parallax error space picture of an undistorted three-dimensional image and a parallax error space picture of a distorted three-dimensional image to be assessed are calculated respectively, then a corresponding three-dimensional gradient amplitude is obtained by calculating the horizontal gradient, the vertical gradient and the view point gradient of each pixel point in the parallax error space picture of the undistorted three-dimensional image, a corresponding three-dimensional gradient amplitude is obtained by calculating the horizontal gradient, the vertical gradient and the view point gradient of each pixel point in the parallax error space picture of the distorted three-dimensional image to be assessed, and ultimately, according to the three-dimensional gradient amplitudes of each pixel point in the two parallax error space pictures, an image quality objective assessment prediction value of the distorted three-dimensional image to be assessed is obtained. The method has the advantages that the obtained three-dimensional gradient amplitudes are very stable and can well reflect quality changing conditions of the three-dimensional images and accordingly correlation of an objective assessment result and subjective perception can be effectively improved.

The invention discloses a panoramic video quality evaluation method. The method comprises the following steps: dividing an original panoramic video and a panoramic video to be evaluated into a plurality of frame groups; projecting the frame groups to six planes of the cube by adopting a cube projection method; calculating spatial domain similarity and frequency domain similarity of each frame group and each projection plane; according to the spatial domain similarity and the frequency domain similarity of all the frame groups and all the projection surfaces, and obtaining the objective evaluation value of the panoramic video to be evaluated through fusion. Complex viewport prediction is avoided through cubic projection, the extracted spatial domain and time domain features have high stability and can well reflect the quality change condition of the panoramic video, and therefore the correlation between the objective evaluation result and subjective perception is effectively improved.

The invention discloses a stereo image quality objective evaluation method based on a gradient structure tensor. The method comprises the following steps of: calculating the gradient structure tensor of each pixel point by calculating a horizontal gradient, a perpendicular gradient and a viewpoint gradient of each pixel point in a left viewpoint image of a stereo image, and performing matrix resolving to obtain a characteristic value and a characteristic vector of the gradient structure tensor of each pixel point; then dividing the left viewpoint image into a sensitive region and a non-sensitive region by using a region detection method; and finally obtaining a final image quality objective evaluation forecast value according to the region type of each pixel. The stereo image quality objective evaluation method has the advantages that the characteristic value and the characteristic vector of the gradient structure tensor are relatively high in stability and can well reflect the quality change of the stereo image; and furthermore, the pixel points in the sensitive region can be evaluated, so that the relativity between an objective evaluation result and subjective perception can be effectively improved.

The invention discloses a stereo image quality objective evaluation method, which comprises the following steps of: performing singular value decomposition on left and right viewpoint images of undistorted stereo images and distorted stereo images, extracting characteristic vectors of the left and right viewpoint images of the distorted stereo images, and performing linear weighting on the characteristic vectors of the left and right viewpoint images to obtain the characteristic vectors of the distorted stereo images; and training the characteristic vectors of the distorted stereo images of the same distortion type in a distorted stereo image set by using support vector regression, and testing each distorted stereo image of the same distortion type by utilizing a support vector regression training mode to obtain image quality objective evaluation predicted values of each distorted stereo image. The method has the advantages of mapping raw data into a high-dimensional characteristic space and performing linear estimation in the high-dimensional characteristic space to construct an optimal linear function so as to avoid the complex process of simulating the related characteristics and mechanism of a human vision system and improve correlation between objective evaluation results and subjective perception.

The invention discloses a stereo image quality objective evaluation method based on visual perception. Firstly, a stereo image is divided into a strong edge block, a weak edge block , a flat block and a texture block, and characteristic information reflecting image quality and depth perception of different zone blocks is extracted through computation so as to obtain stereo image characteristic vectors; and then the characteristic vectors of distorted stereo images of the same distortion type in a distorted stereo image set are trained through support vector regression, and each distorted stereo image of the same distortion type is tested by a support vector regression training model to obtain the objective image quality evaluation forecast value of each distorted stereo image. The method has the advantages that the obtained characteristic vector information reflecting the image quality and the depth perception has stronger stability and can better reflect the quality change condition of the stereo images, and the relevance of an objective evaluation result and subjective perception is improved.

The invention discloses a relocation image quality evaluation method, which considers the influence of structural distortion and content loss on relocation, uses the similarity transformation matrix to establish the transformation relationship between the original image and the relocation image, and calculates the Structural distortion at multiple scales, and calculate the content loss at multiple scales according to the area change of the quadrilateral grid, and then use support vector regression to train the feature vector composed of structural distortion and content loss at multiple scales in the training set, Construct a support vector regression training model; in the test phase, by calculating the feature vector of the relocation image in the test set, and according to the support vector regression training model, the objective quality evaluation prediction value of the relocation image in the test set is predicted. The vector has strong stability and can better reflect the quality change of the relocation image, thus effectively improving the correlation between the objective evaluation result and the subjective perception.

The invention discloses a no-reference objective three-dimensional image quality evaluation method based on binocular visual perception. The method comprises the steps of constructing a converging one-eyed image of a distorted three-dimensional image by using an energy gain control model, and constructing left and right disparity images and indefinite left and right images by using left and right viewpoint images; then extracting a curvelet domain feature from the converging one-eyed image, and separately extracting a generalized Gaussian fitting parameter feature and a lognormal distribution fitting parameter feature from the left and right disparity images and the indefinite left and right images, wherein the three features are used as three-dimensional image feature information; and finally, constructing a relation between three-dimensional image features and average subjective scoring differences through support vector regression to obtain an objective quality evaluation predicted value of the distorted three-dimensional image. The method has the advantages that the acquired feature vector of the distorted three-dimensional image has strong stability and can reflect the quality change condition of the distorted three-dimensional image, the objective evaluation has good consistency with subjective perception of human eyes, and the correlation between the objective evaluation result and the subjective perception is improved.

The invention discloses a preparation method and application of a time-temperature indicator for monitoring temperature and freshness changes in mackerel transportation. The preparation method comprises the following steps: preparation of a Tris-Hcl buffer solution: dissolving tris (hydroxymethyl) aminomethane in water, then adjusting the pH value with hydrochloric acid to form the Tris-Hcl buffer solution, wherein the concentration of the Tris-Hcl buffer solution is 0.05-0.4 mol / l, and the pH value is 7.0. According to the invention, the technical problem of how to monitor the freshness of the prepared time temperature indicator in the cold-chain transportation process by obtaining wide color change and continuously realizing color change for a long time in the range of 0-25 DEG C can be solved.

The invention discloses a tone mapping image quality objective evaluation method based on a global characteristic, wherein the method comprises two processes of a training period and a testing period. Influences of a natural scene statistics characteristic and a color statistics characteristic to tone mapping are considered. A global characteristic vector of a tone mapping image is extracted. Then support vector regression is utilized for training the global characteristic vectors of all tone mapping images in a training image set, thereby constructing a quality predication model. In the testing period, through calculating the global characteristic vector of the tone mapping image for testing, and a quality objective evaluation predicated value of the tone mapping image is obtained through predicating according to the quality predication model which is constructed in the training period. Because the obtained global characteristic vector information has relatively high stability and furthermore can well reflect the quality change condition of the tone mapping image, correlation between an objective evaluation result and subjective perception is effectively improved.

The invention discloses a visual perception-based three-dimensional image quality objective evaluation method which comprises the steps of: firstly, obtaining an objective evaluation measurement value of each pixel point through calculating a local phase characteristic and a local amplitude characteristic of each pixel point in left and right viewpoint images of a three-dimensional image, dividing the three-dimensional image into a shielding region, a binocular inhibition region and a binocular fusion region by a region detection method; and secondly, evaluating all regions respectively and fusing evaluation results to obtain a final image quality objective evaluation prediction value. The visual perception-based three-dimensional image quality objective evaluation method has the advantages that the obtained information for reflecting local phase and local amplitude characteristics has strong stability and can well reflect quality change condition of the three-dimensional image, and the image quality evaluation method of the shielding region, the binocular inhibition region and the binocular fusion region can well reflect the visual perception characteristic of the human visual system, and is effectively improved in correlation of objective evaluation result and subjective perception.

The invention discloses a stereo-image quality objective evaluation method based on a characteristic image. Parallax stereograms of an original and undistorted stereo-image and a distorted and to be evaluated stereo-image are respectively calculated, then by means of the minimum changing image which can be observed by eyes of a left eyepoint image of the distorted and to be evaluated stereo-image and a gradient of disparity image of an anaglyph between a left eyepoint image and a right eyepoint image of the original and undistorted stereo-image, a first structure similarity of the two parallax stereograms is calculated, and an objective evaluation value of the image quality of the distorted and to be evaluated stereo-image is obtained. The stereo-image quality objective evaluation method based on a characteristic image has the advantages that the obtained Parallax stereograms can well reflect the effects of different parallax on stereo-image quality, the structure similarity which is calculated and obtained according to the characteristic image can well reflect the changing conditions of stereo-image quality, the evaluation result is enabled to be more accord with a human visual system, and thereby the correlation of the objective evaluation result and the subjective perception is effectively improved.

The invention discloses a method for evaluating the quality of a down reference three-dimensional video. The method comprises the steps that based on a depth image drawing method, a plurality of virtual viewpoint drawing videos are drawn, a four-dimensional space diagram is constructed, since the constructed four-dimensional space diagram considers the influence of color and depth video distortion to the drawing quality of the virtual viewpoints, so that a three-dimensional video is operated and compared directly to better evaluate the influence of the color and the depth video distortion to the drawing quality of the virtual viewpoints, thereby effectively improving the evaluation performance of the three-dimensional video; and a predicted value of objective quality evaluation of a fuzzy three-dimensional video to be evaluated can be calculated by calculating a coefficient distance and frequency ratio distance information according to the DCT coefficient statistical characteristics of different sub-bands and frequency bands of all four-dimensional space bodies in the four-dimensional space diagram, and thus the quality change condition of the three-dimensional video can be well reflected by less information.

The invention discloses a reference-free three-dimensional picture quality objective evaluation method based on machine learning. The reference-free three-dimensional picture quality objective evaluation method comprises the steps that a vision dictionary list is structured in a training stage, sparse coefficient matrixes of all subblocks in a left viewpoint picture and all subblocks in a right viewpoint picture are calculated respectively for the left view point picture and the right view point picture of any distortion three-dimensional picture according to the structured vision dictionary list, the characteristic vector of the left viewpoint picture and the characteristic vector of the right viewpoint picture are obtained through the maximum pooling method, characteristic extraction is simple, and the computation complexity is low; a support vector regression training model of the left viewpoint picture and a support vector regression training model of the right viewpoint picture are structured, objective quality evaluation predictive values, corresponding to each characteristic vector in a test sample data set, of the left viewpoint picture and the right viewpoint picture respectively are obtained through prediction, weighing is conducted according to characteristic vector information, the objective quality evaluation prediction value of the three-dimensional picture is obtained, and the correlation between the objective evaluation result and subjective perception is high.

The invention discloses an objective evaluation method for the stereo image quality on the basis of image decomposition. The objective evaluation method for the stereo image quality on the basis of the image decomposition comprises the following steps: firstly, respectively decomposing the left viewpoint image of a distorted stereo image to be evaluated into a recovery image and an interference image; decomposing the right viewpoint image of the distorted stereo image to be evaluated into a recovery image and an interference image; respectively evaluating the recovery images of the left viewpoint image and the right viewpoint image by adopting the local phase characteristic and the local vibration amplitude characteristic; respectively evaluating the interference images of the left viewpoint image and the right viewpoint image by using a singular value vector; and obtaining the objective evaluation predicted value for the distorted stereo image quality to be evaluated. The objective evaluation method for the stereo image quality on the basis of the image decomposition has the advantages that the recovery images and the interference images obtained by decomposition can better represent the influence of an image detail and redundant information on the image quality, so that an evaluation result can better conform to the human vision system, and therefore the correlation of an objective evaluation result and subjective perception can be effectively improved.

The invention discloses a method for objectively evaluating the quality of a three-dimensional image based on three-dimensional structural similarity. The method comprises the following steps of: calculating to obtain parallax space maps of an initial undistorted three-dimensional image and a distorted three-dimensional image to be evaluated respectively, calculating to obtain the three-dimensional structural similarity between the parallax space map of the initial undistorted three-dimensional image and the parallax space map of the distorted three-dimensional image to be evaluated, and obtaining the objective evaluation predicted value of the quality of the distorted three-dimensional image to be evaluated. The method has the advantages that the obtained three-dimensional structural similarity can reflect the influence of different parallaxes on the three-dimensional image well, and only a unit with the low three-dimensional structural similarity can be evaluated, so that the objective evaluation result and the correlation of subjective perception are effectively improved.