Department of Computer Science and Technology

Technical reports

Extending lossless image compression

Andrew J. Penrose

December 2001, 137 pages

This technical report is based on a dissertation submitted January 2001 by the author for the degree of Doctor of Philosophy to the University of Cambridge, Gonville & Caius College.

DOI: 10.48456/tr-526


“It is my thesis that worthwhile improvements can be made to lossless image compression schemes, by considering the correlations between the spectral, temporal and interview aspects of image data, in extension to the spatial correlations that are traditionally exploited.”

Images are an important part of today’s digital world. However, due to the large quantity of data needed to represent modern imagery the storage of such data can be expensive. Thus, work on efficient image storage (image compression) has the potential to reduce storage costs and enable new applications.

Many image compression schemes are lossy; that is they sacrifice image informationto achieve very compact storage. Although this is acceptable for many applications, some environments require that compression not alter the image data. This lossless image compression has uses in medical, scientific and professional video processing applications.

Most of the work on lossless image compression has focused on monochrome images and has made use of the spatial smoothness of image data. Only recently have researchers begun to look specifically at the lossless compression of colour images and video. By extending compression schemes for colour images and video, the storage requirements for these important classes of image data can be further reduced.

Much of the previous research into lossless colour image and video compression has been exploratory. This dissertation studies the problem in a structured way. Spatial, spectral and temporal correlations are all considered to facilitate improved compression. This has lead to a greater data reduction than many existing schemes for lossless colour image and colour video compression.

Furthermore, this work has considered the application of extended lossless image coding to more recent image types, such as multiview imagery. Thus, systems that use multiple views of the same scene to provide 3D viewing, have beenprovided with a completely novel solution for the compression of multiview colour video.

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BibTeX record

  author =	 {Penrose, Andrew J.},
  title = 	 {{Extending lossless image compression}},
  year = 	 2001,
  month = 	 dec,
  url = 	 {},
  institution =  {University of Cambridge, Computer Laboratory},
  doi = 	 {10.48456/tr-526},
  number = 	 {UCAM-CL-TR-526}