Visually lossless compression of digitized radiographs based on contrast sensitivity and visual masking

摘要

A visually lossless compression algorithm for digitized radiographs, which predicts the maximum contrast thatwavelet subband quantization distortions can exhibit in the reconstructed image such that the distortions arevisually undetectable, is presented. Via a psychophysical experiment, contrast thresholds were measured for thedetection of 1.15–18.4 cycles/degree wavelet subband quantization distortions in five digitized radiographs; resultsindicate that digitized radiographs impose image- and frequency-selective effects on detection. A quantizationalgorithm is presented which predicts the thresholds for individual images based on a model of visual masking.When incorporated into JPEG-2000 and applied to a suite of images, results indicate that digitized radiographscan be compressed in a visually lossless manner at an average compression ratio of 6.25:1, with some imagesrequiring visually lossless ratios as low as 4:1 and as great as 9:1. The proposed algorithm thus yields imagesthat require the minimum bit-rate such that the reconstructed images are visually indistinguishable from theoriginal images. The primary utility of the proposed algorithm is its ability to provide image-adaptive visuallylossless compression, thereby avoiding overly conservative or overly aggressive compression.