Interactive two-scale color-to-gray

Abstract

Current color-to-gray methods compute the grayscale results by preserving the discriminability among individual pixels. However, human perception tends to firstly group the perceptually similar elements while looking at an image, according to the Gestalt principles. In this paper, we propose a novel two-scale approach for converting color images to grayscale. First, we decompose the input image into multiple soft segments where each segment represents a perceptual group of content. Second, we determine the grayscale of each perceptual group via a global mapping by solving a quadratic optimization. Last, the local details are added into the final result. Our approach is efficient and provides users quick feedback on adjusting the prominent gray tones of the results. As an important aspect of algorithm, our approach offers users an easy, intuitive interactive tool for creating art-like black-and-white images from input color images. Experimental results show that our approach better preserves the overall perception and local details. User studies have been conducted to show the applicability of our approach.