Wavelet-based image coding using a novel morphological framework

Michael T. Orchard; Kannan Ramchandran

doi:10.1117/12.205385

6 April 1995 Wavelet-based image coding using a novel morphological framework

Michael T. Orchard, Kannan Ramchandran

Proceedings Volume 2491, Wavelet Applications II; (1995) https://doi.org/10.1117/12.205385
Event: SPIE's 1995 Symposium on OE/Aerospace Sensing and Dual Use Photonics, 1995, Orlando, FL, United States

Abstract

Wavelet image decompositions generate a tree-structured set of coefficients, providing an hierarchical data-structure for representing images. Recent efforts in image compression have focused on new ways for exploiting dependencies within this hierarchy of wavelet coefficients, and these efforts are achieving significant improvements in coding performance over traditional subband coding approaches. This paper presents a statistical framework for understanding the efficiency of these new zerotree wavelet coding algorithms, and describes our own wavelet coding algorithm which optimally couples scalar and zerotree quantization modes. Building from this framework, we describe a radically new approach to image compression (dubbed morphological representation of wavelet data or MRWD) based on the statistical characterization of morphological sets of wavelet coefficients (a morphological set is a set of coefficients related to other coefficients via morphological operators). Preliminary simulation of the new algorithm shows very promising results.

Citation Download Citation

Michael T. Orchard and Kannan Ramchandran "Wavelet-based image coding using a novel morphological framework", Proc. SPIE 2491, Wavelet Applications II, (6 April 1995); https://doi.org/10.1117/12.205385

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