3D image quality measurement method based on deep learning

Abstract

The invention belongs to the image processing field and provides a novel three-dimensional image quality evaluation method, which can evaluate three-dimensional image quality more accurately and efficiently, and meanwhile, promote development of the stereoscopic imaging technique in a certain extent. According to the technical scheme, the 3D image quality measurement method based on deep learningis characterized by, to begin with, carrying out block segmentation processing on a stereo image data set to obtain a plurality of image blocks, and then, carrying out normalization processing on eachimage block; meanwhile, carrying out principal component analysis (PCA) dimension reduction processing on the stereo image data set to obtain lower-dimension images; then, sending an image block dataset obtained after block segmentation processing and a low-dimension data set obtained after PCA dimension reduction processing to a constructed convolutional neural network; extracting features layer by layer through the convolutional neural network; and finally, obtaining overall quality of the stereo images through a softmax classifier. The method is mainly used for image processing.

Description

technical field [0001] The invention belongs to the field of image processing, and relates to the improvement and optimization of a stereoscopic image quality evaluation method, in particular to the application of deep learning convolutional neural network and principal component analysis in the objective evaluation of stereoscopic image quality. Background technique [0002] With the rapid development of mobile devices and communications, people are exposed to more and more picture content in their lives, especially the recently emerging 3D display technology and related applications have greatly improved the visual experience of the human eye, such as 3D movies, VR glasses, etc., have brought more entertainment and unique experience, which has attracted more researchers not only in the industry, but also in academia. How to effectively evaluate the quality of stereoscopic images in real time has become a hot topic in the field of stereoscopic image research. one of the key...

AI Technical Summary

Problems solved by technology

However, cutting the original large image into small image blocks will destroy the structural information of the original image, thus affecting the accuracy of stereoscopic image quality evaluation.

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