Subband directional vector quantization in radiological image compression

Nabil M. Akrout; Chaouki Diab; Remy Prost; Robert Goutte; Michel Amiel

doi:10.1117/12.59500

1 May 1992 Subband directional vector quantization in radiological image compression

Nabil M. Akrout, Chaouki Diab, Remy Prost, Robert Goutte, Michel Amiel

Proceedings Volume 1653, Medical Imaging VI: Image Capture, Formatting, and Display; (1992) https://doi.org/10.1117/12.59500
Event: Medical Imaging VI, 1992, Newport Beach, CA, United States

Abstract

The aim of this paper is to propose a new scheme for image compression. The method is very efficient for images which have directional edges such as the tree-like structure of the coronary vessels in digital angiograms. This method involves two steps. First, the original image is decomposed at different resolution levels using a pyramidal subband decomposition scheme. For decomposition/reconstruction of the image, free of aliasing and boundary errors, we use an ideal band-pass filter bank implemented in the Discrete Cosine Transform domain (DCT). Second, the high-frequency subbands are vector quantized using a multiresolution codebook with vertical and horizontal codewords which take into account the edge orientation of each subband. The proposed method reduces the blocking effect encountered at low bit rates in conventional vector quantization.

Citation Download Citation

Nabil M. Akrout, Chaouki Diab, Remy Prost, Robert Goutte, and Michel Amiel "Subband directional vector quantization in radiological image compression", Proc. SPIE 1653, Medical Imaging VI: Image Capture, Formatting, and Display, (1 May 1992); https://doi.org/10.1117/12.59500

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