Data compression of color images using a probabilistic linear transform approach

Authors:
Evgeny Gershikov;Moshe Porat
Affiliations:
Technion-Israel Institute of Technology, Haifa, Israel;Technion-Israel Institute of Technology, Haifa, Israel
Venue:
NMA'06 Proceedings of the 6th international conference on Numerical methods and applications
Year:
2006

Citing 5
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Abstract

In this work, we design an efficient algorithm for color image compression using a model for the rate-distortion connection. This model allows the derivation of an optimal color components transform, which can be used to transform the RGB primaries or matrices into a new color space more suitable for compression. Sub-optimal solutions are also proposed and examined. The model can also be used to derive optimal bits allocation for the transformed subbands. An iterative algorithm for the calculation of optimal quantization steps is introduced using the subband rates (entropies). We show that the rates can be approximated based on a probabilistic model for subband transform coefficients to reduce the algorithm's complexity. This is demonstrated for the Discrete Cosine Transform (DCT) as the operator for the subband transform and the Laplacian distribution assumption for its coefficients. The distortion measure considered is the MSE (Mean Square Error) with possible generalization to WMSE (Weighted MSE). Experimental results of compressed images are presented and discussed for two versions of the new compression algorithm.