Paper
7 May 1997 Effects of quantization and truncation strategies on image quality during lossy image compression
Binsheng Zhao, Peter Klaus Kijewski
Author Affiliations +
Abstract
Alternative strategies used for wavelet-based lossy image compression can affect lesion detection differently at higher compression ratios. These effects were studied using three variants of a wavelet-based image compression algorithm: (1) unified quantization, (2) truncation of all coefficients at all subbands, and (3) truncation of coefficients subband by subband. The nonprewhitening- matched-filter-derived da, a deductibility index, was used to quantify the changes in detection performance as a function of compression ratio for each strategy. Based on this approach, the optimal compression strategy was determined. Two classes of images were generated to simulate signal-present and signal-absent cases for a liver imaged by CT. For each strategy, the performance in discriminating between the signal-present class and signal-absent class was quantified by da for varying compression ratios. Among the three strategies studied, truncation of all coefficients is the least desirable strategy for preserving small, low contrast signals; truncation of coefficients subband by subband yields the best result for subtle signals, but distorts high frequency edges between tissues; unified quantization is the best strategy if both low contrast objects and high frequency edges are to be preserved.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Binsheng Zhao and Peter Klaus Kijewski "Effects of quantization and truncation strategies on image quality during lossy image compression", Proc. SPIE 3031, Medical Imaging 1997: Image Display, (7 May 1997); https://doi.org/10.1117/12.273961
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KEYWORDS
Image compression

Signal detection

Quantization

Wavelets

Image quality

Liver

Interference (communication)

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