Lossless compression of CFA sampled image using decorrelated Mallat wavelet packet decomposition

Yeejin Lee, Keigo Hirakawa, Truong Q. Nguyen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Scopus citations

Abstract

This paper presents a rigorous analysis of wavelet transform on color filter array (CFA) sampled images. The presented analysis suggests that the wavelet coefficients of HL and LH subbands are highly correlated. Hence, we propose a novel lossless compression scheme for CFA sampled images using the decorrelated Mallat wavelet packet decomposition. We validated our theoretical analysis and the performance of the proposed compression scheme using images of natural scenes captured in a raw format. The experimental results verify that our proposed method improves coding efficiency relative to the standard and the state-of-the-art lossless compression schemes CFA sampled images.

Original languageEnglish
Title of host publication2017 IEEE International Conference on Image Processing, ICIP 2017 - Proceedings
PublisherIEEE Computer Society
Pages2721-2725
Number of pages5
ISBN (Electronic)9781509021758
DOIs
StatePublished - 2 Jul 2017
Event24th IEEE International Conference on Image Processing, ICIP 2017 - Beijing, China
Duration: 17 Sep 201720 Sep 2017

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume2017-September
ISSN (Print)1522-4880

Conference

Conference24th IEEE International Conference on Image Processing, ICIP 2017
Country/TerritoryChina
CityBeijing
Period17/09/1720/09/17

Keywords

  • Camera processing pipeline
  • Color filter array
  • Image compression
  • JPEG
  • Lossless coding
  • Wavelet transform

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