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Brian Schmanske

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Proceedings Article | 22 May 2003 Paper

Bit-plane-channelized hotelling observer for predicting task performance using lossy-compressed images

Brian Schmanske, Murray Loew

Proceedings Volume 5034, (2003) https://doi.org/10.1117/12.480082

KEYWORDS: Image compression, Signal detection, Performance modeling, Signal to noise ratio, Wavelets, Mammography, Image quality, Image analysis, Chromium, Spatial resolution

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A technique for assessing the impact of lossy wavelet-based image compression on signal detection tasks is presented. A medical image’s value is based on its ability to support clinical decisions such as detecting and diagnosing abnormalities. Image quality of compressed images is, however, often stated in terms of mathematical metrics such as mean square error. The presented technique provides a more suitable measure of image degradation by building on the channelized Hotelling observer model, which has been shown to predict human performance of signal detection tasks in noise-limited images. The technique first decomposes an image into its constituent wavelet subband coefficient bit-planes. Channel responses for the individual subband bit-planes are computed, combined,and processed with a Hotelling observer model to provide a measure of signal detectability versus compression ratio. This allows a user to determine how much compression can be tolerated before signal detectability drops below a certain threshold.

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