only have one example from the ensemble, it is necessary to estimate the histogram at each point from surrounding
Adaptive histogram equalization has become well-established as a technique for enhancing contrast in images. This paper pixel GLs. In windowed adaptive HE this is done by calcuinvestigates an alternative formulation of histogram equalizalating the cumulative distribution within a window around tion. An implementation of this is presented. The resulting each pixel to find its transformed GL. In a previous paper algorithm involves the application of a filter to a set of image [7] the HE process was analyzed using a model-based fields, and the potential for filtering these fields differently framework. The values of the mapping function for a GL is illustrated through the restoration of a deliberately decan be found by filtering the input image thresholded by graded image. Hence the alternative algorithm is shown to be that GL. This was shown to be a method of estimating the effective and to provide a framework for improved estimation of ideal value for each location by filtering across neighboring the optimal gray-level mappings over standard methods.