Title :
Distortion-limited vector quantization
Author :
Hahn, Peter J. ; Mathews, V.John
Author_Institution :
Dept. of Electr. Eng., Utah Univ., Salt Lake City, UT, USA
Abstract :
This paper presents a vector quantization system that limits the maximum distortion introduced to a pre-selected threshold value. This system uses a recently introduced variation of the L∞ distortion measure that attempts to minimize the occurrences of quantization errors above a preselected threshold. The vectors are first coded using the new distortion measure. The quantization error vectors in which at least one entry is above the threshold are again coded using a residual vector quantizer. The pixels of the input image where the quantisation errors are still above the threshold are scalar quantized to force all the errors under the specified threshold. An experimental result is included in which all the error magnitudes are constrained to be below fifteen. This image was coded using 0.85 bits per pixel with a relatively simple multiplier-free vector quantizer and without entropy coding
Keywords :
image coding; vector quantisation; L∞ distortion measure; distortion-limited vector quantization; image coding; multiplier-free vector quantizer; pre-selected threshold value; quantization errors; residual vector quantizer; Adaptive systems; Cities and towns; Distortion measurement; Entropy coding; Humans; Image coding; NASA; Nearest neighbor searches; Pixel; Vector quantization;
Conference_Titel :
Data Compression Conference, 1996. DCC '96. Proceedings
Conference_Location :
Snowbird, UT
Print_ISBN :
0-8186-7358-3
DOI :
10.1109/DCC.1996.488339