Abstract

A filtering algorithm for fast image enhancement is described. The algorithm tries to make the minimum modification on the original image structures while it performs noise smoothing at a given filtering level. The filtered image is a weighted combination of four subimages obtained from low-pass filtering the original image along four major directions. The weighting on each subimage is controlled by the differences between these subimages and the original image The resulting image is then nonsymmetrically sharpened to enhance the image structure boundaries, The overall effect of this filtering structure is effective adaptive noise reduction and edge enhancement with an efficient implementation using array processors. The high regularity and parallelism of the algorithm also makes it suitable for its efficient implementation using very large scale integrated (VLSI) circuits or multiprocessor systems. The performance of the algorithm in effectively reducing image noise and preserving/enhancing important image structures is discussed and demonstrated using several MR images from a low-field-strength MR imaging system.

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