17 April 1995 Psychophysical evaluation of the effect of JPEG, full-frame discrete cosine transform (DCT) and wavelet image compression on signal detection in medical image noise
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Abstract
Image quality associated with image compression has been either arbitrarily evaluated through visual inspection, loosely defined in terms of some subjective criteria such as image sharpness or blockiness, or measured by arbitrary measures such as the mean square error between the uncompressed and compressed image. The present paper psychophysically evaluated the effect of three different compression algorithms (JPEG, full-frame, and wavelet) on human visual detection of computer-simulated low-contrast lesions embedded in real medical image noise from patient coronary angiogram. Performance identifying the signal present location as measure by d' index of detectability decreased for all three algorithms by approximately 30% and 62% for the 16:1 and 30:1 compression rations respectively. We evaluated the ability of two previously proposed measures of image quality, mean square error (MSE) and normalized nearest neighbor difference (NNND), to determine the best compression algorithm. The MSE predicted significantly higher image quality for the JPEG algorithm in the 16:1 compression ratio and for both JPEG and full-frame for the 30:1 compression ratio. The NNND predicted significantly high image quality for the full-frame algorithm for both compassion rations. These findings suggest that these two measures of image quality may lead to erroneous conclusions in evaluations and/or optimizations if image compression algorithms.
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Miguel P. Eckstein, Craig A. Morioka, James Stuart Whiting, Neal L. Eigler, "Psychophysical evaluation of the effect of JPEG, full-frame discrete cosine transform (DCT) and wavelet image compression on signal detection in medical image noise", Proc. SPIE 2436, Medical Imaging 1995: Image Perception, (17 April 1995); doi: 10.1117/12.206838; https://doi.org/10.1117/12.206838
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