Abstract
In this paper we proposed Independent histogram equalization (HE) method is used to enhance the hidden image detail and to increase the contrast of input image having a low dynamic range as well as preserve the mean brightness of the image. Such technique used optimal threshold method to partition the original image histogram before applying HE. This is much able to produce better result of output image than the original image by increasing the gray level difference (i.e. contrast) among object and background. The genetic algorithm determines the values of the Gaussian function parameters which further evaluates the threshold value for the partitioning of the histogram. It overcomes the drawback of HE technique because it is unable to preserve the average brightness of the image. In theory, after applying HE the average brightness shift towards the middle of the gray scale. This is the major drawback of HE.
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