Comparison of Different Enhanced Image Denoising with Multiple Histogram Techniques
Sandeep Kumar1, Puneet Verma2
1Sandeep Kumar, Deptt. of ECE, Hindu College of engineering, Sonepat, India.
2Puneet Verma, A.P, Deptt. of ECE, Hindu College of engineering, Sonepat, India.
Manuscript received on April 15, 2012. | Revised Manuscript received on April 20, 2012. | Manuscript published on May 05, 2012. | PP: 208-213 | Volume-2 Issue-2, May 2012 . | Retrieval Number: B0556042212/2012©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: There are different techniques for enhance an image by using gray scale manipulation, histogram equalization and filtering. Out of different enhancement techniques HE became a popular technique because, it is simple and effective. For preserving the input brightness of the image, there is a segment to avoid the generation of non-existing artifacts in the output image. So, these methods are used for preserving the input brightness with the significant contrast enhancement. They may produce an image which is not look like input image. HE method is used for re-mapping of the gray level and tends to introduce some annoying artifacts and unnatural enhancement. To preserve from these drawbacks brightness preserving techniques are used such as CLAHE, DSIHE and DHE. But after the enhancement some noise is also there which is further reduce for better result. Enhanced Image Denoising comparative analysis with the different techniques is carried out. In this comparison some subjective and objective parameters are used. For subjective parameter visual quality and computation time and for objective parameter PSNR and MSE are used.
Keywords: Contrast enhancement, HE, PSNR, MSE, visual quality .