Combining Color Constancy and Gamma Correction for Image Enhancement

In this paper, image enhancement issues are addressed by analyzing the effect of two well-known color constancy algorithms in combination with gamma correction. Those effects are studied applying the algorithms separately and in combination. Images from the Barnard dataset and from the Berkeley dataset are considered for experimental tests. The performance of the approaches is evaluated comparing the Average Power Spectrum Value of the test images and their corresponding outcomes, as a quality measure. According to the experimental results, it is observed that the application of the gamma correction after a color constancy algorithm results in an improved image quality.

I. Introduction

Color is an important cue for computer vision and image processing related topics, like feature extraction [1], human-computer interaction [2], and color appearance models [3]. Colors observed in images are determined by the intrinsic properties of objects and surfaces, as well as the color of the illuminant. For a robust color-based system, the effects of the illumination should be filtered out [4].