Image Coder Based on Hilbert Scanning of Embedded quadTrees
Data Compression Conference (DCC), IEEE Computer Society, page 470 - 2011
In this work we present an effective and computationally simple algorithm for image compression based on Hilbert Scanning of Embedded quadTrees (Hi-SET). It allows to represent an image as an embedded bitstream along a fractal function. Embedding is an important feature of modern image compression algorithms, in this way Salomon in [1, pg. 614] cite that another feature and perhaps a unique one is the fact of achieving the best quality for the number of bits input by the decoder at any point during the decoding. Hi-SET possesses also this latter feature. Furthermore, the coder is based on a quadtree partition strategy, that applied to image transformation structures such as discrete cosine or wavelet transform allows to obtain an energy clustering both in frequency and space. The coding algorithm is composed of three general steps, using just a list of significant pixels.
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BibTex references
@Article\{MoO2011, author = "Jes\'us Jaime Moreno Escobar and Xavier Otazu", title = "Image Coder Based on Hilbert Scanning of Embedded quadTrees", journal = "Data Compression Conference (DCC), IEEE Computer Society", pages = "470", year = "2011", keywords = "Fractals, Image Coding, Image Compression, Quadtrees, Wavelet Transforms", abstract = "In this work we present an effective and computationally simple algorithm for image compression based on Hilbert Scanning of Embedded quadTrees (Hi-SET). It allows to represent an image as an embedded bitstream along a fractal function. Embedding is an important feature of modern image compression algorithms, in this way Salomon in [1, pg. 614] cite that another feature and perhaps a unique one is the fact of achieving the best quality for the number of bits input by the decoder at any point during the decoding. Hi-SET possesses also this latter feature. Furthermore, the coder is based on a quadtree partition strategy, that applied to image transformation structures such as discrete cosine or wavelet transform allows to obtain an energy clustering both in frequency and space. The coding algorithm is composed of three general steps, using just a list of significant pixels.", keywords = "Fractals, Image Coding, Image Compression, Quadtrees, Wavelet Transforms", url = "http://cic.uab.cat/Public/Publications/2011/MoO2011" }