Histogram Equalization Based Mean Self - Adaptive Plateau Histogram Equalization for Brightness Preserving and Contrast Enhancement

Histogram Equations (HE) is a simple and effective method for contrast enhancement as it can automatically define the intensity transformation function based on statistical characteristics of the image. Where preservation of the original brightness is essential to avoid annoying artefacts, HE tends to alter the brightness of the entire image and it stretches the contrast of the high histogram regions, and compresses the contrast of the low histogram regions. HE also produces saturation effects by extremely pushing the intensities towards the right or the left side of the histogram. Plateau Histogram Equalization (PHE) or Clipping Histogram Equalization (CHE) is a technique to implement the HE to overcome these drawbacks. In the present paper, a adapted method of Self-Adaptive Plateau Histogram Equalization (SAPHE), developed with mean filter and mean threshold value is described and compared the experimental results with Histogram Equalization (HE), Bi- Histogram Equalization with Plateau Limit (BHEPL), Self-Adaptive Plateau Histogram Equalization (SAPHE) and Modified Self-Adaptive Plateau Histogram Equalization (Modified SAPHE) by using image quality measures such as Absolute Mean Brightness Error (AMBE) and Peak-Signal to Noise Ratio (PSNR).