Grayscale image contrast enhancement based on multi-scale edge representation

We propose an image contrast enhancement algorithm using multi-scale edge representation of images. It has long been known that the Human Vision System (HVS) heavily depends on edges in the understanding and perception of scenes. Contrasts in grayscale images are measured between the differences of pixels on both sides of edges, which is defined as the gradient magnitudes of those edges. And multi-scale edge of an image is characterized by the local extrema of wavelet coefficients across levels. So rebuilding an image from properly stretched the extrema is a promising way to enhance the contrast of the image. We tackle this reconstruction problem with a straightforward interpolation method instead of the commonly used iterative projection process. Extensive experiments justify our algorithm an efficient and effective contrast enhancement method.