Improving reversible color-to-grayscale conversion with halftoning

Zi Xin Xu, Yuk Hee Chan

Research output: Journal article publicationJournal articleAcademic researchpeer-review

10 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)111-123
Number of pages13
JournalSignal Processing: Image Communication
Publication statusPublished - 1 Mar 2017


  • Color palette
  • Color quantization
  • Halftoning
  • Information hiding
  • Noise shaping
  • Reversible color mapping

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering


Dive into the research topics of 'Improving reversible color-to-grayscale conversion with halftoning'. Together they form a unique fingerprint.

Cite this