ERT Image Evaluation Based on Sparse Representation Algorithm

Bo Song, Pai Wang, Jaqing Li

Abstract


Most of the existing image quality evaluation is to extract image features, and then use support vector regression, sparse representation and other algorithms to evaluate the image quality. In this paper, an adaptive sub-dictionary image evaluation algorithm based on sparse representation is used. By extracting relevant image features such as gradient features and color features, a complete dictionary is first constructed using the features, and then a sparse representation method based on the sub-dictionary is used to obtain the sparse corresponding to the ERT image. Coefficient, the final image quality score is obtained by the corresponding formula.

Keywords


sparse representation, Sub-dictionary, OMP algorithm, image quality evaluation


DOI
10.12783/dtetr/mcaee2020/35026

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