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Technical Report

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Technical Report Number



Adaptive histogram equalization (ahe) is a method for adaptive contrast enhancement of digital images propped by Pizer et. Al.. It has the properties that it is an automatic, reproducible method for the simultaneous viewing of contrast within a digital image with a large dynamic range. Recent experiments have show that in specific cases, there is no significant difference in the ability of ahe and linear intensity windowing to display grey-scale contrast. More recently, Pizer et al. have proposed a variant of ahe which limits the allowed contrast enhancement of the image. The contrast-limited adaptive histogram equalization (clahe) produces images in which the noise content of an image is nor excessively enhanced, but in which sufficient contrast is provided for the visualization of structures within the image. Images processed with clahe have a more natural appearance and facilitate the comparison of different areas of an image. However, the reduced contrast enhancement of clahe may hinder the ability of an observer to detect the presence of some significant grey-scale contrast. In this work, a psychophysical observer experiment was performed to determine if there is a significant difference in the ability of ahe and clahe to depict grey-scale contrast. Observers were presented with CT images of the chest processed with ahe and clahe into some of which subtle artificial lesions were introduced. The observers were asked to rate their confidence regarding the presence of the lesions; this rating-scale data was analyzed using Receiver Operating Characteristic curving techniques. These ROC curves were compared for significant differences in the observers' performances. In this study, no difference was found in the abilities of ahe and clahe to depict contrast information.


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