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Lossy compression using wavelets, block DCT, and lapped orthogonal transforms optimized with a perceptual model

We implemented and compared the performance of three lossy compression techniques for the compression of x-ray radiographs. The quantization matrices for each technique was optimized based on a perceptual model developed by Watson. We examined the ability of the perceptual model to identify the just noticeable difference compression point and compare the performance of the perceptual model to a commonly used metric, signal to noise ratio. We also examined the compression performance of the perceptually optimized techniques at the just noticeable difference level of compression. As a benchmark, the compression performance was compared to the SPIHT wavelet compression algorithm. We found that the wavelet based perceptual model provided the most consistent estimate of the just noticeable difference threshold, the block DCT based technique was next, and signal to noise ratio was significantly worse. The compression performance was similar, at the just noticeable difference point, though block DCT provided slightly better compression than the wavelet technique, which in turn provided slightly better compression than the SPIHT wavelet compression algorithm.