It appears you don't have support to open PDFs in this web browser. To view this file, Open with your PDF reader
Abstract
In this paper, we have proposed a novel image enhancement technique based on M band wavelets. The conventional image enhancement algorithms opt for contrast enhancement using equalization techniques. Contrast enhancement is one of the most important issues in image enhancement techniques. High difference in luminance reflected from two adjacent surfaces results in a good contrast image which makes the object more distinguishable from other objects in the background. Many a times owing to over contrast, minute details of the images are lost; which cannot be tolerated for biomedical images. Moreover, they don't account for the noise embedded in the images. Also denoising using conventional filters result in blurring of images. The proposed algorithm not only denoises the image by retaining the high frequency edges, but also increases the contrast and generates a high resolution image. Various parameters like MSE and PSNR are been taken into account for comparison of enhanced images generated from the proposed algorithm with that of the conventional techniques.
You have requested "on-the-fly" machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Show full disclaimer
Neither ProQuest nor its licensors make any representations or warranties with respect to the translations. The translations are automatically generated "AS IS" and "AS AVAILABLE" and are not retained in our systems. PROQUEST AND ITS LICENSORS SPECIFICALLY DISCLAIM ANY AND ALL EXPRESS OR IMPLIED WARRANTIES, INCLUDING WITHOUT LIMITATION, ANY WARRANTIES FOR AVAILABILITY, ACCURACY, TIMELINESS, COMPLETENESS, NON-INFRINGMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Your use of the translations is subject to all use restrictions contained in your Electronic Products License Agreement and by using the translation functionality you agree to forgo any and all claims against ProQuest or its licensors for your use of the translation functionality and any output derived there from. Hide full disclaimer