Abstract

A novel algorithm, histogram shifting (HS) is presented, which performs edge detection or edge enhancement with the choice of two parameters. The histogram of a region surrounding each pixel is found and translated toward the origin, resulting in the new pixel value. Images from a variety of medical imaging modalities were processed with HS to perform detection and enhancement of edges. Comparison with results obtained from conventional edge detection (e.g., Sobel) and with conventional edge-enhancement algorithms is discussed. HS appears to perform the edge-detection operation without introducing "double-edge" effects often obtained with conventional edge-detection algorithms. HS also appears to perform edge enhancement without introducing extensive noise artifacts, which may be noticeable with many edge-enhancement algorithms.

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