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Image quality blind evaluation method

A technology of image quality and blind evaluation, applied in image enhancement, image analysis, image data processing, etc., can solve the problems of low accuracy of visual impact evaluation, inability to mix image degradation type judgment, etc., and achieve the effect of improving accuracy

Active Publication Date: 2017-06-09
SHANGHAI ADVANCED RES INST CHINESE ACADEMY OF SCI
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AI Technical Summary

Problems solved by technology

[0006] In view of the shortcomings of the prior art described above, the purpose of the present invention is to provide a blind image quality evaluation method, which is used to solve the problem that the blind image quality evaluation method in the prior art cannot judge the degradation type of mixed images and its visual Low accuracy of impact assessment and difficulty in application in multimedia systems

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Embodiment Construction

[0028] Embodiments of the present invention are described below through specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific implementation modes, and various modifications or changes can be made to the details in this specification based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, in the case of no conflict, the following embodiments and features in the embodiments can be combined with each other.

[0029] It should be noted that the diagrams provided in the following embodiments are only schematically illustrating the basic ideas of the present invention, although only the components related to the present invention are shown in the diagrams rather than the number, shape and shape of the ...

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Abstract

The invention provides an image quality blind evaluation method. The image quality blind evaluation method comprises the steps of 1), extracting a characteristic of a quality-reduced image block in a training image, and estimating an offset between the characteristic of the image block and the characteristic of a non-quality-reduced image block; 2), analyzing different types of quality reduction in a probability latent semantic analysis method, and mapping the different types of quality reduction to different theme distribution characteristics, wherein the different types of quality reduction comprise single quality reduction and hybrid quality reduction; 3), establishing a relation between an image theme distribution characteristic and the image quality based on the image training set according to a machine learning method, thereby forming a quality blind evaluation model for a hybrid quality reduction image; and 4), evaluating the quality of the quality reduction image outside the training set by means of the quality blind evaluation model. The image quality blind evaluation method has advantages of improving accuracy in no-parameter quality evaluation, setting a problem of evaluating the hybrid quality reduction image in engineering, and realizing high suitability of comprehensive evaluation for image acquisition, compression and transmission performance in a multimedia system on the condition that an original image cannot be acquired.

Description

technical field [0001] The invention relates to the technical field of image quality evaluation, in particular to a blind image quality evaluation method. Background technique [0002] Image subjective quality evaluation is a research hotspot and has a very wide range of applications. The acquisition, transmission and decoding process of image / video will introduce certain distortion and reduce the subjective quality of the image. The computer-aided evaluation of image quality can help to find the design defects of the multimedia system, guide users to adjust the system, and then ensure that users get satisfactory image quality. There is a gap between the traditional image quality evaluation method based on signal-to-noise ratio and people's subjective perception of the image, which cannot reflect the image quality well. In recent years, the research on image quality evaluation is mainly divided into two categories: with reference and without reference. [0003] The parame...

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Application Information

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IPC IPC(8): G06T7/00
CPCG06T7/0002G06T2207/20081G06T2207/30168
Inventor 刘立庄赵丹张浩
Owner SHANGHAI ADVANCED RES INST CHINESE ACADEMY OF SCI
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