Camera-Aware Multi-Resolution Analysis for Raw Image Sensor Data Compression

Yeejin Lee, Keigo Hirakawa, Truong Q. Nguyen

Research output: Contribution to journalArticlepeer-review

23 Scopus citations

Abstract

We propose novel lossless and lossy compression schemes for color filter array (CFA) sampled images based on the Camera-Aware Multi-Resolution Analysis, or CAMRA. Specifically, by CAMRA we refer to modifications that we make to wavelet transform of CFA sampled images in order to achieve a very high degree of decorrelation at the finest scale wavelet coefficients; and a series of color processing steps applied to the coarse scale wavelet coefficients, aimed at limiting the propagation of lossy compression errors through the subsequent camera processing pipeline. We validated our theoretical analysis and the performance of the proposed compression schemes using the images of natural scenes captured in a raw format. The experimental results verify that our proposed methods improve coding efficiency relative to the standard and the state-of-the-art compression schemes for CFA sampled images.

Original languageEnglish
Pages (from-to)2806-2817
Number of pages12
JournalIEEE Transactions on Image Processing
Volume27
Issue number6
DOIs
StatePublished - Jun 2018

Keywords

  • Camera processing pipeline
  • color filter array
  • image compression
  • JPEG
  • wavelet transform

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