2D histogram The number of pairs of adjacent pixels with value and in the input image.

1. CONTRAST ENHANCEMENT BASED ON LAYERED DIFFERENCE REPRESENTATION Chulwoo Lee, Chul Lee, and Chang-Su Kim School of Electrical Engineering, Korea University , Seoul, Korea Overview Inter-Layer Aggregation Intra-Layer Optimization By , we have a linear equation, • Global contrast enhancement Proposed approach Conventional approach For example, • Constrained optimization problem Gray-level intensity Gray-level difference • Solution to the problem • Quadratic cost function • The active-set method Basic Concept • 2D histogram • The number of pairs of adjacent pixels with value and in the input image. First, we need to smooth the obtained by the Gaussian kernel Input image Output image A large Frequent gray-level pairs Increase difference variable Image contrast is enhanced • Proportional relationship : Normalizing constant Elementary Properties Then, we aggregate by the weighted averaging process Experimental Results : user-controllable parameter, e.g. and and Relationship between Relationship between • Objective assessment for • Subjective assessment By summing up for all possible ’s, At layer 1 At layer 2 At layer Estimation of (a) Original (b) WTHE[1] (c) WAHE[2] (d) Proposed [1] Q. Wang and R. K. Ward, “Fast Image/Video Contrast Enhancement Based on Weighted Thresholded Histogram Equalization,” IEEE Trans. Consum. Electron., vol. 53, no. 2, pp. 757–764, 2007. [2] T. Arici, S. Dikbas, and Y. Altunbasak, “A Histogram Modification Framework and Its Application for Image Contrast Enhancement,” IEEE Trans. Image Process., vol. 18, no. 9, pp. 1921–1935, 2009. {wiserain, kayne, changsukim} @ korea.ac.kr