Iterative sharpening for image contrast enhancement
Ali Alsam, Ivar Farup, Hans Jakob Rivertz · 2015
In this paper, the problem of iterative sharpening for local contrast enhancement is addressed. We present a fast algorithm that spreads the high frequencies of an image to successively lower resolutions resulting in an improvement in sharpness and local contrast. The algorithm is similar to the well established unsharp masking with certain fundamental differences. The image is blurred with a Gaussian filter and a difference image representing the hight frequencies is calculated. This difference is then amplified and added back to the blurred image and the process is repeated without altering the original high frequencies. Our result demonstrate that up to 100 iterations can be applied without image artifacts.