λ-enhancement: contrast adaptation based on optimization of image fuzziness
Hamid R. Tizhoosh, Gerald Krell, B. Michaelis · 2002
The contrast improvement of the digital images is an important task in image processing and machine vision. The gray-level modification is one of the most popular methods to perform image enhancement because it is simple in implementation and fast in computing. Since the selection of a suitable mathematical function for the gray-level transformation depends on the specific grayness properties of the image, it is necessary to develop some techniques for automatic selection of an appropriate function. In this work, we introduce a new algorithm for contrast adaptation (/spl lambda/-enhancement) which is based on involutive fuzzy complements and measures of fuzziness. Regarding to the amount of grayness ambiguity the proposed technique detects the suitable form of the gray-level modification in the set of involutive membership function generated by parameter /spl lambda/.