Iterative image coding with overcomplete complex wavelet transforms

Nick G. Kingsbury; Tanya Reeves

doi:10.1117/12.509901

23 June 2003 Iterative image coding with overcomplete complex wavelet transforms

Nick G. Kingsbury, Tanya Reeves

Proceedings Volume 5150, Visual Communications and Image Processing 2003; (2003) https://doi.org/10.1117/12.509901
Event: Visual Communications and Image Processing 2003, 2003, Lugano, Switzerland

Abstract

Overcomplete transforms, such as the Dual-Tree Complex Wavelet Transform, can offer more flexible signal representations than critically-sampled transforms such as the Discrete Wavelet Transform. However the process of selecting the optimal set of coefficients to code is much more difficult because many different sets of transform coefficients can represent the same decoded image. We show that large numbers of transform coefficients can be set to zero without much reconstruction quality loss by forcing compensatory changes in the remaining coefficients. We develop a system for achieving these coding aims of coefficient elimination and compensation, based on iterative projection of signals between the image domain and transform domain with a non-linear process (e.g.~centre-clipping or quantization) applied in the transform domain. The convergence properties of such non-linear feedback loops are discussed and several types of non-linearity are proposed and analyzed. The compression performance of the overcomplete scheme is compared with that of the standard Discrete Wavelet Transform, both objectively and subjectively, and is found to offer advantages of up to 0.65 dB in PSNR and significant reduction in visibility of some types of coding artifacts.

Citation Download Citation

Nick G. Kingsbury and Tanya Reeves "Iterative image coding with overcomplete complex wavelet transforms", Proc. SPIE 5150, Visual Communications and Image Processing 2003, (23 June 2003); https://doi.org/10.1117/12.509901

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