Fitting quantization scheme to multiresolution detail preserving compression algorithm

Artur Przelaskowski


An adaptive space-frequency quantization scheme in a scalar fashion applied to wavelet-based compression is presented. Because of strong demands due to detail preservation in lossy image archiving and transmission, as in for example medical applications, different modifications of uniform threshold quantization are considered. The main features of the elaborated procedure are as follows: fitting the threshold value to the local data characteristics in a backward way and quantization step size estimation for each subband as a forward and backward framework in the optimization procedure. Many tests conducted with a real wavelet compression scheme confirm the significant efficiency of the presented quantization procedures. The achieved total compression effectiveness is promising in spite of the simple coding algorithm
Author Artur Przelaskowski RE
Artur Przelaskowski,,
- The Institute of Radioelectronics
Book Proceedings of the IEEE-SP International Symposium on Time-Frequency and Time-Scale Analysis, 1998, 1998
Keywords in Englishadaptive signal processing, adaptive space-frequency quantization, backward framework, biomedical equipment, bit rate, coding algorithm, Compression algorithms, context modeling, data compression, Efficiency, forward framework, image coding, image resolution, local data characteristics, lossy image archiving, lossy image transmission, medical applications, Medical services, multiresolution detail preserving compression algorithm, optimisation, optimization procedure, quantisation (signal), quantization, quantization step size estimation, real wavelet compression, scalar quantization, spatial resolution, subband, Testing, Tests, threshold value, transform coding, uniform threshold quantization, wavelet-based compression, Wavelet domain, wavelet transforms
Score (nominal)1
Citation count*2 (2013-01-30)
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