Stereoscopic image quality evaluation method based on sparse reconstructed color fusion image

Abstract

The invention belongs to the field of image processing, and provides a stereoscopic image quality evaluation method based on sparse reconstructed color fusion image. This method not only has good consistency with the human eye subjective MOS value, but also is more suitable to evaluate the asymmetric distortion stereoscopic image, and promote the development of stereoscopic imaging technology on acertain basis. As such, that present invention, Stereo image quality evaluation method based on sparse reconstructed color fusion image, At first, a color fusion image is obtain, using color fusion images to learn and train dictionaries, The distorted color fusion image is reconstructed on the trained complete dictionary D, and the corresponding color fusion image is used for information compensation. Then, the spatial entropy and spectral entropy features of the reconstructed fusion image and the corresponding color fusion image are extracted, and the two features are weighted to obtain thefinal features. Finally, the final mass fraction is obtained by support vector machine SVR. The invention is mainly applied to image processing.

Description

technical field [0001] The invention belongs to the field of image processing and relates to image fusion, construction of a sparse dictionary and optimization and improvement of a stereoscopic image quality evaluation method. Background technique [0002] With the rapid development of multimedia imaging and display technology, stereoscopic imaging technology has received a lot of attention and research. In the process of acquisition, transmission, compression, recovery and display of stereoscopic images, some distortion will inevitably be introduced. How to evaluate the degree of distortion of stereoscopic images and how to evaluate the quality of stereoscopic image processing technology are important issues worth discussing. The stereoscopic image quality evaluation method can solve the above problems. [0003] At present, stereoscopic image quality evaluation mainly includes subjective quality evaluation and objective quality evaluation. Subjective quality evaluation h...

AI Technical Summary

Problems solved by technology

However, this fusion image is obtained by a simple method that does not fully conform to the characteristics of the human brain, and there is currently no accurate method for obtaining parallax, and it is not easy to obtain a good parallax compensation image

Literature [18] evaluates the stereoscopic image quality by amplitude and phase, but the amplitude and phase cannot represent the fusion image well

And the fused image obtained by the above method is a grayscale fused image, which may lose the corresponding color information

In addition, the above fusion methods are not good for the evaluation of asymmetrically distorted stereo images.

However, in the actual image shooting process, due to objective reasons such as camera performance errors, it cannot be guaranteed that the brightness and chromaticity of the left and right viewpoint images captured by the two cameras at the same time are exactly the same, so the stereoscopic image with asymmetric distortion will be more widespread.

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