IEEE Trans Image Process - Reduced-reference image quality assessment by structural similarity estimation.

Tópicos

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Resumo

Reduced-reference image quality assessment (RR-IQA) provides a practical solution for automatic image quality evaluations in various applications where only partial information about the original reference image is accessible. Here we propose an RR-IQA method by estimating the structural similarity (SSIM) index, which is a widely used full-reference (FR) image quality measure shown to be a good indicator of perceptual image quality. Specifically, we extract statistical features from a multi-scale, multi-orientation divisive normalization transform and develop a distortion measure by following the philosophy in the construction of SSIM. We found an interesting linear relationship between the FR SSIM measure and our RR estimate when the image distortion type is fixed. A regression-bydiscretization method is then applied to normalize our measure across image distortion types. We use six publiclyavailable subject-rated databases to test the proposed RR-SSIM method, which shows strong correlations with both SSIM and subjective quality evaluations. Finally, we introduce the novel idea of partially repairing an image using RR features and use deblurring as an example to demonstrate its application.

Resumo Limpo

reducedrefer imag qualiti assess rriqa provid practic solut automat imag qualiti evalu various applic partial inform origin refer imag access propos rriqa method estim structur similar ssim index wide use fullrefer fr imag qualiti measur shown good indic perceptu imag qualiti specif extract statist featur multiscal multiorient divis normal transform develop distort measur follow philosophi construct ssim found interest linear relationship fr ssim measur rr estim imag distort type fix regressionbydiscret method appli normal measur across imag distort type use six publiclyavail subjectr databas test propos rrssim method show strong correl ssim subject qualiti evalu final introduc novel idea partial repair imag use rr featur use deblur exampl demonstr applic

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