Spatially-selective quantization and coding for wavelet-based image compression

Recent developments in psychovisual modeling have led to improvements in wavelet-based coder performance. A spatially selective quantizer based on texture masking sensitivities is introduced, which hides distortion in high-contrast portions of images. Unlike other spatial quantization schemes, this method requires explicit side information to convey stepsizes. A simple coder is presented which leverages this side information to reduce the rate required to code the quantized data. Side information coding is also discussed. With respect to visual quality, this compression scheme performs competitively with a CSF-optimized JPEG-2000 coder at equivalent rates.