Quality image metrics for synthetic images based on perceptual color differences

Stéphane Albin, Gilles Rougeron, Bernard Péroche, Alain Trémeau

IEEE Transactions on Image Processing · 2002 · 15 citations · 29 references

Concepts

TL;DR

Advances in image rendering and the growing need for quantitative comparison of synthetic color images make perceptually based metrics essential for objective visual quality assessment. The paper proposes a new methodology that defines three objective image quality metrics to address this need. The methodology employs the LLAB color space, a CIELab1976 modification, and introduces three metrics: a pixel‑by‑pixel local distance map, a global value, and a recursive subdivision adaptive distance map that is coarser but cheaper to compute.

Abstract

Due to the improvement of image rendering processes, and the increasing importance of quantitative comparisons among synthetic color images, it is essential to define perceptually based metrics which enable to objectively assess the visual quality of digital simulations. In response to this need, this paper proposes a new methodology for the determination of an objective image quality metric, and gives an answer to this problem through three metrics. This methodology is based on the LLAB color space for perception of color in complex images, a modification of the CIELab1976 color space. The first metric proposed is a pixel by pixel metric which introduces a local distance map between two images. The second metric associates, to a pair of images, a global value. Finally, the third metric uses a recursive subdivision of the images to obtain an adaptative distance map, rougher but less expensive to compute than the first method.

References

29