Lossless compression of color filter array mosaic images with visualization via JPEG 2000

Miguel Herńandez-Cabronero, Michael W. Marcellin, Ian Blanes, Joan Serra-Sagrista

Research output: Contribution to journalArticlepeer-review

22 Scopus citations


Digital cameras have become ubiquitous for amateur and professional applications. The raw images captured by digital sensors typically take the form of color filter array (CFA) mosaic images, which must be "developed" (via digital signal processing) before they can be viewed. Photographers and scientists often repeat the "development process" using different parameters to obtain images suitable for different purposes. Since the development process is generally not invertible, it is commonly desirable to store the raw (or undeveloped) mosaic images indefinitely. Uncompressed mosaic image file sizes can be more than 30 times larger than those of developed images stored in JPEG format. Thus, data compression is of interest. Several compression methods for mosaic images have been proposed in the literature. However, they all require a custom decompressor followed by development-specific software to generate a displayable image. In this paper, a novel compression pipeline that removes these requirements is proposed. Specifically, mosaic images can be losslessly recovered from the resulting compressed files, and, more significantly, images can be directly viewed (decompressed and developed) using only a JPEG 2000 compliant image viewer. Experiments reveal that the proposed pipeline attains excellent visual quality, while providing compression performance competitive to that of state-of-The-Art compression algorithms for mosaic images.

Original languageEnglish (US)
Article number8012476
Pages (from-to)257-270
Number of pages14
JournalIEEE Transactions on Multimedia
Issue number2
StatePublished - Feb 2018


  • Bayer color filter array (cfa)
  • Color filter arrays
  • Image compression
  • Jpeg 2000

ASJC Scopus subject areas

  • Signal Processing
  • Media Technology
  • Computer Science Applications
  • Electrical and Electronic Engineering


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