Digital Image Denoising Using Histogram and Dynamic Filters

International Journal of Computer & Organization Trends (IJCOT)          
© 2014 by IJCOT Journal
Volume - 4 Issue - 1
Year of Publication : 2014
Authors :  Kamlesh Dixit , Mohit Khandelwal
DOI :  10.14445/22492593/IJCOT-V5P301


Kamlesh Dixit , Mohit Khandelwal. "Digital Image Denoising Using Histogram and Dynamic Filters", International Journal of Computer & organization Trends (IJCOT), V4(1):27-30 Jan - Feb 2014, ISSN:2249-2593, Published by Seventh Sense Research Group.


Digital Image Denoising is one of the most important and difficult techniques in image research. The aim of image Denoising is to improve the visual appearance of an image, or to provide a “better transform representation for another automated image processing. Many images like medical images, satellite images, aerial images and even real life photographs suffer from poor contrast and noise. It is necessary to enhance the contrast and remove the noise to increase image quality. One of the most important stages in medical images detection and analysis is image Denoising techniques which improves the quality of images for human viewing, removing blurring and noise, increasing contrast, etc.


[1] M.Elad and M.Aharon, Image Denoising via sparse and redundant representation over learned dictionaries, IEEE T IP 15(12) Pp. 3736-3745, 2006.
[2] T S Cho, C L Zitnic et al. “Image restoration by matching gradientdistributions”, IEEE T-PAMI, 34(4):683–694, 2012.
[3] N.Mohanapriya,B.Kaalavati, “Comparative Study Of Enhancement Techniques for Medical Images”, IJCA, vol.61, No.20, January 2013. [3] B. Klein, S. Rati Khandelwal “Various Image Enhancement Techniques- A Critical Review” International Journal of Advanced Research in Computer and Communication Engineering, Pp. 1605-1609 Vol. 2, Issue 3, March 2013
[4] S S Bedil Saikaley, “Imaging, characterization and processing with laxicon derivatives” The School of Graduate Studies Laurentian University Sudbury, Ontario, Canada 2013.
[5] P.C Rossin. Image processing in frequency Domain. Lehigh UniversityURL: Accessed January 2011.
[6] Agaian, SOSS., Blair Silver,Karen A.Panetta. “Transform Coefficient Histogram-Based Image Enhancement Algorithms Using Contrast Entropy”, IEEE Transaction on Image Processing, Vol. 16, No. 3, March 2007.


Digital Image Denoising, Histogram, Image filter