Fitting quantization scheme to multiresolution detail preserving compression algorithm
AbstractAn 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
|Book||Proceedings of the IEEE-SP International Symposium on Time-Frequency and Time-Scale Analysis, 1998, 1998|
|Keywords in English||adaptive 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|
|Citation count*||2 (2013-01-30)|
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.