A novel contrast enhancement algorithm based on the layered difference representation of 2-D histograms is proposed in this work. We attempt to enhance image contrast by amplifying the gray-level differences between adjacent pixels. To this end, we obtain the 2-D histogram h(k,k+l) from an input image, which counts the pairs of adjacent pixels with gray-levels k and k+l, and represent the gray-level differences in a tree-like layered structure. Then, we formulate a constrained optimization problem based on the observation that the gray-level differences, occurring more frequently in the input image, should be more emphasized in the output image. We first solve the optimization problem to derive the transformation function at each layer. We then combine the transformation functions at all layers into the unified transformation function, which is used to map input gray-levels to output gray-levels. Experimental results demonstrate that the proposed algorithm enhances images efficiently in terms of both objective quality and subjective quality.
Chulwoo Lee, Chul Lee, and Chang-Su Kim, “Contrast enhancement based on layered difference representation,” in Proc. International Conference on Image Processing (ICIP), Orlando, USA, pp. 965-968, Sept.-Oct. 2012. [doi] [pdf] [pptx]
Chulwoo Lee, Chul Lee, and Chang-Su Kim, “Contrast enhancement based on layered difference representation of 2D histograms,” IEEE Transactions on Image Processing, vol. 22, no. 12, pp. 5372-5384, Dec. 2013. [doi] [pdf]
7 of 4.2.0x from The USCI-SIPI Image Database, Volume 3: Miscellaneous
69 captured images from commercial digital cameras: Download (15.3 MB)
4 synthetic images: Download (445 kB)