Spatial Domain Image Enhancement using Cloud Model for Suppressing Impulse Noise
Main Article Content
Abstract
Impulse noise corrupts the image when it is sensing from a malfunctioning camera, storing in a fault memory or sending through a
noisy channel. As images are giving useful information in every field, image denoising plays a key role in image processing. Median filters
are preferred for removal of impulse noise. Existing methods suppress noise randomly without considering whether the pixel is “noisy†or not.
This paper proposes a method for effective noise suppression by understanding uncertainties in noisy image. There are two stages in this
method. First stage identifies the corrupted pixels via uncertainty based detector where as second stage suppresses the noise candidates by
using weighted fuzzy mean filter compared with the traditional switched hashing filters. The proposed method provides good results
subjectively and objectively. As the proposed filter can restore the image with good detail preservation at a high noise level, great
improvement results in image denoising.
keywords: Cloud model (CM), image denoising, impulse noise, median filter, weighted fuzzy mean filter, uncertainties, peak signal to
noise ratio(PSNR).
Downloads
Article Details
COPYRIGHT
Submission of a manuscript implies: that the work described has not been published before, that it is not under consideration for publication elsewhere; that if and when the manuscript is accepted for publication, the authors agree to automatic transfer of the copyright to the publisher.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work
- The journal allows the author(s) to retain publishing rights without restrictions.
- The journal allows the author(s) to hold the copyright without restrictions.