Adaptive inter color residual prediction for efficient red-green-blue intra coding

Jinwoo Jeong, Yoonsik Choe, Yong Goo Kim

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


Intra coding of an RGB video is important to many high fidelity multimedia applications because video acquisition is mostly done in RGB space, and the coding of decorrelated color video loses its virtue in high quality ranges. In order to improve the compression performance of an RGB video, this paper proposes an inter color prediction using adaptive weights. For making full use of spatial, as well as inter color correlation of an RGB video, the proposed scheme is based on a residual prediction approach, and thus the incorporated prediction is performed on the transformed frequency components of spatially predicted residual data of each color plane. With the aid of efficient prediction employing frequency domain inter color residual correlation, the proposed scheme achieves up to 24.3 of bitrate reduction, compared to the common mode of H.264/AVC high 4:4:4 intra profile.

Original languageEnglish
Article number077404
JournalOptical Engineering
Issue number7
Publication statusPublished - 2011 Jul

Bibliographical note

Funding Information:
All authors have completed and submitted the International Committee of Medical Journal Editors form for disclosure of potential conflicts of interest. Amy K. Feehan receives research support from the Louisiana Public Health Institute. Joshua L. Denson reports grants from the American Diabetes Association, research funding from the Gordon and Betty Moore Foundation, the Society of Critical Care Medicine, and the National Institutes of Health (NIH); and personal fees from Astrazeneca, GlaxoSmithKline, and Guidepoint Global, outside the current work. Jason P. Block reports a grant from the National Institute of Diabetes and Digestive and Kidney Diseases, NIH and receipt of honoraria for participating in a panel discussion for the Kenner Foundation on “Early Detection of Pancreatic Cancer.” No other potential conflicts of interest were disclosed.

Funding Information:
PCORnet, the National Patient-Centered Clinical Research Network; Patient-Centered Outcomes Research Institute.

All Science Journal Classification (ASJC) codes

  • Atomic and Molecular Physics, and Optics
  • Engineering(all)


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