Differential lossless encoding of images using non-linear predictive techniques

Nasir Memon, Sibabrata Ray, Khalid Sayood

Research output: Contribution to journalConference articlepeer-review


We investigate the problem of constructing a prediction scheme for a given image that results in the minimum zero-order entropy of prediction errors. The problem is formulated as a combinatorial optimization problem. This allows the use of some well known techniques from combinatorial optimization in order to construct heuristic solutions. We describe a few heuristics and give preliminary implementation results. The techniques developed can also be generalized in a straight forward manner to composite source modeling where the data is modeled as an interleaved sequence emanating from k different sub-sources. Although the problems and proposed solutions are described in a strictly deterministic manner, they can also be formulated in a stochastic framework to yield solutions that are valid for a family of images emitted by the same source.

Original languageEnglish (US)
Article number413728
Pages (from-to)841-845
Number of pages5
JournalProceedings - International Conference on Image Processing, ICIP
StatePublished - 1994
EventThe 1994 1st IEEE International Conference on Image Processing - Austin, TX, USA
Duration: Nov 13 1994Nov 16 1994

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing


Dive into the research topics of 'Differential lossless encoding of images using non-linear predictive techniques'. Together they form a unique fingerprint.

Cite this