Decolorizing images for robust matching

Even though the color contains important distinctive information, it is mostly neglected in many fundamental vision applications (such as image matching) since the standard grayscale conversion (luminance channel) is employed extensively. This paper introduces a novel image decolorization technique that besides performing a perceptually accurate color mapping as the other state-of-the-art operators did, it focuses to increase as well the local contrast by manipulating effectively the chromatic information. Additionally, we perform an extensive evaluation of the several recent SIFT-derived local operators in context of image matching when the camera viewpoint is varied and images are differently decolorized based on several recent grayscale operators. The experiments prove the effectiveness of our approach that is able to decolorize accurately images but also to improve the matching results.