Translator Disclaimer
1 September 1995 Quantization noise reduction using wavelet thresholding for various coding schemes
Author Affiliations +
We propose a nonlinear, wavelet-based method to efficiently improve the performance of various coding schemes for lossy image data compression. Coarse quantization of the transform coefficients often results in some undesirable artifacts, such as ringing effect, contouring effect and blocking effect, especially at very low bit rate. The decoding can be viewed as a typical statistical estimation problem of reconstructing the original image signal from the decomposed image, a noisy observation, using the classical signal processing model of `signal plus additive noise'. We perform the wavelet-domain thresholding on the decompressed image to attenuate the quantization noise effect while maintaining the relatively sharp features (e.g. edges) of the original image. Experimental results show that de-noising using the undecimated discrete wavelet transform achieves better performance than using the orthonormal discrete wavelet transform, with an acceptable computational complexity (O(MNlog2(MN)) for an image of size M X N). Both the objective quality and the subjective quality of the reconstructed image are significantly improved with the reduction of coding artifacts. In addition, dithering technique can be embedded in the encoding scheme to achieve further improvement of the visual quality.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Dong Wei, Markus Lang, Haitao Guo, Jan Erik Odegard, and C. Sidney Burrus "Quantization noise reduction using wavelet thresholding for various coding schemes", Proc. SPIE 2569, Wavelet Applications in Signal and Image Processing III, (1 September 1995);

Back to Top