Analysis and Comparison of Various Contrast Enhancement Techniques

Contrast enhancement assumes an important part in image processing which makes an image more clear and bright. It essentially improves the image quality which makes the image's content easy to recognize. In this paper the analysis of four popular contrast enhancement techniques have been done to overcome the brightness and preservation issues and also keeps up the quality of the image. These four techniques are Histogram Equalization (HE), Brightness Preserving Bi- Histogram Equalization (BBHE), Contrast Limited Adaptive Histogram Equalization (CLAHE), and Recursive Mean-Separate Histogram Equalization (RMSHE). Additionally the work also shows the estimation of various parameters like: Signal to noise ratio (SNR), Mean square error (MSE), Root mean square error (RMSE), Mean absolute error (MAE), Peak signal to noise ratio (PSNR), and Structure similarity index (SSIM) for each technique.