Improving reversible color-to-grayscale conversion with halftoning

作者:

Highlights:

摘要

Reversible color-to-grayscale conversion (RCGC) aims at embedding the chromatic information of a full color image into its grayscale version such that the original color image can be reconstructed in the future when necessary. Conventional RCGC algorithms tend to put their emphasis on the quality of the reconstructed color image, which makes the color-embedded grayscale image visually undesirable and suspicious. This paper presents a novel RCGC framework that emphasizes the quality of both the color-embedded grayscale image and the reconstructed color image simultaneously. Its superiority against other RCGC algorithms is mainly achieved by developing a color palette that fits into the application and exploiting error diffusion to shape the quantization noise to high frequency band. The improved quality of the color-embedded grayscale image makes the image appears as a normal image. It does not catch the attention of unauthorized people and hence the embedded chromatic information can be protected more securely.

论文关键词:Reversible color mapping,Information hiding,Halftoning,Color quantization,Color palette,Noise shaping

论文评审过程:Received 24 August 2016, Revised 29 November 2016, Accepted 20 December 2016, Available online 24 December 2016, Version of Record 17 January 2017.

论文官网地址:https://doi.org/10.1016/j.image.2016.12.005