Dequantenhancement by spatial color algorithms.

Abstract

Spatial color algorithms (SCAs) are algorithms grounded in the retinex theory of color sensation that, mimicking the human visual system, perform image enhancement based on the spatial arrangement of the scene. Despite their established role in image enhancement, their potential as dequantizers has never been investigated. Here, we aim to assess the effectiveness of SCAs in addressing the dual objectives of color dequantization and image enhancement at the same time. To this end, we propose the term dequantenhancement. In this paper, through two experiments on a dataset of images, SCAs are evaluated through two distinct pathways: first, quantization followed by filtering to assess both dequantization and enhancement; and second, filtering applied to original images before quantization as further investigation of mainly the dequantization effect. The results are presented both qualitatively, with visual examples, and quantitatively, through metrics including the number of colors, retinal-like subsampling contrast (RSC), and structural similarity index (SSIM).