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Grey conversion via perceived-contrast

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Abstract

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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Authors and Affiliations

  1. Department of Mathematics, Zhejiang University, Hangzhou, 310027, China

    Wei Zhu & Ruizhen Hu

  2. School of Mathematical Sciences, University of Science and Technology of China, Anhui, 230026, China

    Ligang Liu

Authors
  1. Wei Zhu
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  2. Ruizhen Hu
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  3. Ligang Liu
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Correspondence to Wei Zhu.

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Zhu, W., Hu, R. & Liu, L. Grey conversion via perceived-contrast. Vis Comput 30, 299–309 (2014). https://doi.org/10.1007/s00371-013-0854-9

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