A Fast Implementation of Adaptive Histogram Equalization

Abstract

Adaptive histogram equalization (AHE) is a popular and effective algorithm for image contrast enhancement. But it's quite computationally expensive and time consuming. In this paper, a fast implementation of AHE based on pure software techniques is proposed. Three accelerative techniques are combined to form the new fast AHE: first, local histogram is acquired by an iterative approach with a sliding window; second, in computing cumulative histogram function, not more than half of the histogram is cumulated; Third, by keep the block size W2 equal to the product of grey level number and integral power of 2, all the multiplication and division operations are replaced with fast bitwise shift. Both theoretical analysis and experimental results demonstrate the proposed algorithm is effective