Transform-based quality assessment for enhanced image

V. Voronin; E. Semenishchev; A. Zelensky; O. Tokareva; Y. Cen; S. Agaian

doi:10.1117/12.2598321

1 August 2021 Transform-based quality assessment for enhanced image

V. Voronin, E. Semenishchev, A. Zelensky, O. Tokareva, Y. Cen, S. Agaian

Proceedings Volume 11842, Applications of Digital Image Processing XLIV; 118422G (2021) https://doi.org/10.1117/12.2598321
Event: SPIE Optical Engineering + Applications, 2021, San Diego, California, United States

Conference Poster

Abstract

Images captured in bad weather suffer from low contrast and faint color. Recently, plenty of enhanced algorithms have been proposed to improve visibility and restore color. The goal of image quality assessment is to predict the perceptual quality for improving imaging systems' performance. We proposed a no-reference image quality enhancement measure using hypercomplex Fourier transform for color images. The main idea is that enhancing the contrast of an image would create more high-frequency content in the enhanced image than the original image. An increase in the magnitude of higher frequency coefficients indicates an enhancement in contrast to the image's luminance content. To test the performance of the proposed algorithm, the public database TID2013 is used. The Pearson rank-ordered correlation coefficient is utilized to measure and compare the proposed quality measure's performance with state-of-the-art approaches.

Citation Download Citation

V. Voronin, E. Semenishchev, A. Zelensky, O. Tokareva, Y. Cen, and S. Agaian "Transform-based quality assessment for enhanced image", Proc. SPIE 11842, Applications of Digital Image Processing XLIV, 118422G (1 August 2021); https://doi.org/10.1117/12.2598321

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