Date of Publication :30th March 2018

Abstract: The quality of an image is mostly affected due to weather, lighting or equipment that has been used for image capture. Image enhancement is the process of adjusting or enhancing the digital images by altering its structural features like contrast and resolution so that the results are more suitable for display or further image analysis. The enhancement process includes removal of noise, sharpen or brighten the image and making it clearer to identify the key features. In this paper, Image Enhancement techniques such as Point processing and Histogram Equalization techniques are reviewed and discussed. Point processing operations contain image negative, contrast stretching, thresholding transformation, gray level slicing, logarithmic transformation and power-law transformation. Under Histogram Equalization, Contrast Limited Adaptive Histogram Equalization (CLAHE), Equal Area Dualistic Sub-Image Histogram Equalization (DSIHE), Dynamic Histogram Equalization (DHE) Algorithms are reviewed. The concepts of all these techniques are discussed, compared and their performances are evaluated based on the parameters Absolute Mean Brightness Error (AMBE), Contrast and Peak-Signal-to-Noise-Ratio (PSNR) values

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