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A method for subjective evaluation results of image quality based on fuzzy clustering statistics

A technology for image quality and subjective evaluation, applied in image enhancement, image analysis, image data processing, etc.

Active Publication Date: 2018-12-14
CHANGCHUN INST OF OPTICS FINE MECHANICS & PHYSICS CHINESE ACAD OF SCI
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Problems solved by technology

[0013] Aiming at the problems existing in the methods of statistical image quality subjective evaluation results of existing databases such as TID2013, the embodiment of the present invention proposes a method for statistical image quality subjective evaluation results based on fuzzy clustering

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  • A method for subjective evaluation results of image quality based on fuzzy clustering statistics
  • A method for subjective evaluation results of image quality based on fuzzy clustering statistics
  • A method for subjective evaluation results of image quality based on fuzzy clustering statistics

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[0030] In order to enable those skilled in the art to better understand the solutions of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only It is an embodiment of a part of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present invention.

[0031] The terms "first", "second", "third", "fourth", etc. (if any) in the description and claims of the present invention and the above drawings are used to distinguish similar objects and not necessarily Describe a specific order or sequence. It is to be understood that the terms so used are interchangeable under appropriate cir...

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Abstract

The embodiment of the invention discloses a method for subjective evaluation results of image quality based on fuzzy clustering statistics. The core idea of this method is that the different subjective evaluation scores obtained from the image can be regarded as the matching degree between the image and each score. The fuzzy similarity matrix of image sequence is established by the similarity relation of sample image score, and fuzzy clustering analysis is realized. After the best classification of sample image is determined, the image sequence is the final evaluation result of image quality.This method is suitable for subjective evaluation of image quality with large sample size. The method also provides the dynamic clustering diagram of the sample image, and displays the clustering process of the image for the user to refer. The user can change the threshold value according to the use demand, and reclassify the image and score.

Description

technical field [0001] The invention relates to the technical field of image quality evaluation in image recognition, in particular to a method for subjective evaluation results of image quality based on fuzzy cluster statistics. Background technique [0002] Image is the main source for artificial intelligence to obtain external information. In the process of acquisition, storage and display, due to the influence of factors such as noise, defocus, packet loss and color distortion, the image quality will be reduced to varying degrees. Image quality directly affects the acquisition of computer information. Therefore, the evaluation method of image quality has important research significance. It has been widely used in camera automatic dimming and focusing, image or video compression, reconstruction, enhancement and other technologies, as well as computer vision. , machine learning and other fields. [0003] The image quality database is a measure of the image quality evaluat...

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Application Information

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IPC IPC(8): G06T7/00G06K9/62
CPCG06T7/0002G06T2207/30168G06F18/23213
Inventor 郭劲王伟国刘廷霞刘阳王鹤琪
Owner CHANGCHUN INST OF OPTICS FINE MECHANICS & PHYSICS CHINESE ACAD OF SCI
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