21 April 1995 Image coding based on energy-sorted wavelet packets
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Proceedings Volume 2501, Visual Communications and Image Processing '95; (1995) https://doi.org/10.1117/12.206717
Event: Visual Communications and Image Processing '95, 1995, Taipei, Taiwan
Abstract
The discrete wavelet transform performs multiresolution analysis, which effectively decomposes a digital image into components with different degrees of details. In practice, it is usually implemented in the form of filter banks. If the filter banks are cascaded and both the low-pass and the high-pass components are further decomposed, a wavelet packet is obtained. The coefficients of the wavelet packet effectively represent subimages in different resolution levels. In the energy-sorted wavelet- packet decomposition, all subimages in the packet are then sorted according to their energies. The most important subimages, as measured by the energy, are preserved and coded. By investigating the histogram of each subimage, it is found that the pixel values are well modelled by the Laplacian distribution. Therefore, the Laplacian quantization is applied to quantized the subimages. Experimental results show that the image coding scheme based on wavelet packets achieves high compression ratio while preserving satisfactory image quality.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Lin-Wen Kong, Lin-Wen Kong, Kuen-Tsair Lay, Kuen-Tsair Lay, } "Image coding based on energy-sorted wavelet packets", Proc. SPIE 2501, Visual Communications and Image Processing '95, (21 April 1995); doi: 10.1117/12.206717; https://doi.org/10.1117/12.206717
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