The simulation results show that MMSICHE method outperforms other HE methods in terms of various image quality measures, i.e. This method avoids excessive enhancement and produces images with natural enhancement. ![]() ![]() This method achieves multi objective of preserving brightness as well as image information content (entropy) along with control over enhancement rate, which in turn suits for consumer electronics applications. (iii) The clipped histogram is first bisected based on median intensity then further divided into four sub images based on individual mean intensity, subsequently performing histogram equalization for each sub image. ![]() (ii) The histogram is clipped using a plateau limit set as the median of the occupied intensity. The proposed algorithm undergoes three steps: (i) The Median and Mean brightness values of the image are calculated. This paper presents a robust contrast enhancement algorithm based on histogram equalization methods named Median-Mean Based Sub-Image-Clipped Histogram Equalization (MMSICHE).
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