On the modeling of DCT and subband image data for compression

1 January 1995

journal article
Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Image Processing

Vol. 4 (2) , 186-193
https://doi.org/10.1109/83.342184

Abstract

Image subband and discrete cosine transform coefficients are modeled for efficient quantization and noiseless coding. Quantizers and codes are selected based on Laplacian, fixed generalized Gaussian, and adaptive generalized Gaussian models. The quantizers and codes based on the adaptive generalized Gaussian models are always superior in mean-squared error distortion performance but, generally, by no more than 0.08 bit/pixel, compared with the much simpler Laplacian model-based quantizers and noiseless codes. This provides strong motivation for the selection of pyramid codes for transform and subband image coding.

Keywords

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