The anisotropic wavelet packet transform is an extension of the conventional wavelet (packet) transform where the basis can have different scales in different dimensions. As there are certain kinds of images with different behaviour in horizontal and vertical direction, anisotropic wavelet packet bases can be adapted more precisely to these images. Zero-tree image compression has already proved its efficiency on conventional wavelet transformed data as well as for wavelet packets. In this work, zero-tree methods are extended to work with anisotropic wavelet packets and coding results are shown for several types of images.
This paper presents a wavelet based codec (SMAWZ) that uses the most important features of the SPIHT algorithm (zero-trees) while eliminating all concepts that are incompatible with a reduced hardware environment. This is done by replacing dynamic list structures with static maps (significance maps) which leads to a simpler and spacially oriented coefficient scan order. Additionally, extensions such as wavelet packet support and object based coding are included.
KEYWORDS: Wavelet transforms, Lithium, Video, Image compression, Video compression, Laser induced plasma spectroscopy, Video coding, Linear filtering, Digital filtering, Computing systems
The wavelet transform is more and more widely used in image and video compression. One of the best known algorithms in image compression is the SPIHT algorithm which involves the wavelet transform. As today the parallelization of the wavelet transform is sufficiently investigated this work deals with the parallelization of the compression algorithm itself as a next step.
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