GENERALIZED IMAGE-CONTRAST ENHANCEMENT TECHNIQUE BASED ON THE HEINEMANN CONTRAST DISCRIMINATION MODEL

This paper presents a generalized image contrast enhancement technique , which equalizes the perceived brightness distribution based on the H einemann contrast discrimination model It is based on the mathematical ly proven existence of a unique solution to a nonlinear equation, and is formulated with easily tunable parameters. The model uses a two-ste p log-log representation of luminance contrast between targets and sur round in a luminous background setting. The algorithm consists of two nonlinear gray scale mapping functions that have seven parameters, two of which are adjustable Heinemann constants. Another parameter is the background gray level. The remaining four parameters are nonlinear fu nctions of the gray-level distribution of the given image, and can be uniquely determined once the previous three are set Tests have been ca rried out to demonstrate the effectiveness of the algorithm for increa sing the overall contrast of radiology images. The traditional histogr am equalization can be reinterpreted as an image enhancement technique based on the knowledge of human contrast perception. In fact it is a special case of the proposed algorithm. (C) 1996 SPIE and IS&T.