Problem statement: Image enhancement improves an image appearance by increasing dominance of some features or by decreasing ambiguity between different regions of the image. Histogram based image enhancement technique is mainly based on equalizing the histogram of the image and increasing the dynamic range corresponding to the image. Approach: Histogram Equalization is widely used in different ways to perform contrast enhancement in images. As a result, such image creates side-effects such as washed out appearance and false contouring due to the significant change in brightness. In order to overcome these problems, mean brightness preserving Histogram Equalization based techniques have been proposed. Generally, these methods partition the histogram of the original image into sub histograms and then independently equalize each sub histogram with Histogram Equalization. Results: The comparison of recent histogram based techniques is presented for contrast enhancement in low illumination environment and the experiment results are collected using low light environment images. Conclusion: The histogram modification algorithm is simple and computationally effective that makes it easy to implement and use in real time systems.
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