Grey conversion via perceived-contrast

This paper presents a new color-to-gray conversion algorithm capturing the perceived appearance of color images. Based on the Filter Theory, we formulate a novel measurement of channel-level distinction, called Channel Salience, to depict the filter level of three color stimuli. This salience metric guides a contrast adjustment process to enhance the perceived grayscale in the final output with a two-steps conversion. Experimental results show that our algorithm produces pleasing results for a variety of color images and we further extend the Channel Salience to edge detection.

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