Aims: The manuscript aims at designing and developing a model for optimum contrast
enhancement of an input image. The output image of model ensures the minimum noise, the maximum
brightness and the maximum entropy preservation.
Objectives: * To determine an optimal value of threshold by using the concept of entropy maximization
for segmentation of all types of low contrast images. * To minimize the problem of over enhancement
by using a combination of weighted distribution and weighted constrained model before
applying histogram equalization process. * To provide an optimum contrast enhancement with minimum
noise and undesirable visual artefacts. * To preserve the maximum entropy during the contrast
enhancement process and providing detailed information recorded in an image. * To provide the
maximum mean brightness preservation with better PSNR and contrast. * To effectively retain the
natural appearance of an images. * To avoid all unnatural changes that occur in Cumulative Density
Function. * To minimize the problems such as noise, blurring and intensity saturation artefacts.
Methods: 1. Histogram Building. 2. Segmentation using Shannon’s Entropy Maximization. 3.
Weighted Normalized Constrained Model. 4. Histogram Equalization. 5. Adaptive Gamma Correction
Process. 6. Homomorphic Filtering.
Results: Experimental results obtained by applying the proposed technique MEWCHE-AGC on the
dataset of low contrast images, prove that MEWCHE-AGC preserves the maximum brightness,
yields the maximum entropy, high value of PSNR and high contrast. This technique is also effective
in retaining the natural appearance of an images. The comparative analysis of MEWCHE-AGC with
existing techniques of contrast enhancement is an evidence for its better performance in both qualitative
as well as quantitative aspects.
Conclusion: The technique MEWCHE-AGC is suitable for enhancement of digital images with varying
contrasts. Thus useful for extracting the detailed and precise information from an input image.
Thus becomes useful in identification of a desired regions in an image.
Keywords: Optimum Contrast Enhancement, Shannon`s Entropy, Weighted Constrained, Adaptive Gamma Correction, Homomorphic
Filtering, Maximum Entropy, Brightness Preservation.
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