Title :
Hilbert scan and image compression
Author :
Biswas, Sambhunath
Author_Institution :
Machine Intelligence Unit, Indian Stat. Inst., Calcutta, India
Abstract :
The use of the Hilbert scan is relatively new in image compression. This scan is guided by the Hilbert space filling curve. A Hilbert image, thus produced by this scan of a gray level image provides better compression rate than that of a raster scanned image. Since a Hilbert image is a 1D image, an efficient 1D algorithm based on a Bezier-Bernstein polynomial has been developed to simultaneously separate out and and approximate homogeneous segments of pixels depending on some absolute error based criteria. The approximation parameters are then encoded by a Huffman coding scheme. Investigation shows that better performance on image compression can be achieved using the Hilbert scan. Comparison with an existing algorithm shows also better performance of the proposed algorithm
Keywords :
Huffman codes; approximation theory; data compression; image coding; polynomials; 1D image; Bezier-Bernstein polynomial; Hilbert image; Hilbert scan; Hilbert space filling curve; Huffman coding scheme; absolute error based criteria; compression rate; gray level image; image compression; Filling; Hilbert space; Huffman coding; Image coding; Image processing; Image resolution; Image segmentation; Machine intelligence; Pixel; Polynomials;
Conference_Titel :
Pattern Recognition, 2000. Proceedings. 15th International Conference on
Conference_Location :
Barcelona
Print_ISBN :
0-7695-0750-6
DOI :
10.1109/ICPR.2000.903522