Automatic analysis system and method for subjective image quality evaluation

Abstract

The invention discloses an automatic analysis system and method for subjective image quality evaluation. The automatic analysis system comprises an image grouping module, an image description module,a problem region segmentation module, an image quality evaluation module, and an evaluation report generation module. The image grouping module is used for carrying out group division on inputted original images based on scenes to obtain different image groups. The image description module is used for carrying out image description on image groups obtained by the image grouping module respectively. The problem region segmentation module divides the image into different problem regions according to the image description obtained by the image description module. The image quality evaluation module carries out image quality analysis based on the statistic features and contents of the problem regions and provides various problem analysis results for different problems. The evaluation report generation module generates an evaluation report including analysis results of all scenes and analysis results of all problems.

Description

technical field [0001] The invention belongs to the field of subjective evaluation of image quality, and can obtain evaluation results and generate evaluation reports by analyzing pictures of the same scene taken by different models. Background technique [0002] The current subjective evaluation process of image quality in this field includes: [0003] 1. Testers use different shooting equipment to take photos in the same scene; [0004] 2. The testers group and name the pictures according to the scene and send them to the image quality experts; [0005] 3. Image quality experts analyze the image quality of the same group of pictures according to multiple indicators; [0006] 4. According to the analysis results, select the images and areas with problems, typesetting and generating reports. [0007] The above methods can achieve subjective evaluation of image quality and have been used in practical projects for several years, but the disadvantages are: [0008] 1. The i...

AI Technical Summary

Problems solved by technology

[0008] 1. The image processing process such as grouping photos by testers and experts selecting appropriate images and regions for report writing is too cumbersome and time-consuming;

[0009] 2. The number of image quality experts is small, and with the rapid update of device versions with camera functions, the amount of image quality evaluation tasks has increased dramatically

However, it takes a long period of time to train professional image quality experts according to the traditional method, and it is difficult to meet the demand;

[0010] 3. Subjective errors of image quality experts are unavoidable,

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