Noise Reduction in Compressed Images Using Improved Fuzzy Transform Technique
Main Article Content
Abstract
In the area of digital image compression, computer
algorithms are used to perform processing of images and
compression. It deals with developing a digital system that
perform operations on digital image. It has many advantages using
in digital camera, film, Satellite, X-ray and many more
applications. Image compression is a technique used to save the
storage space normally used to compress images and videos.
Number of compression algorithms are used like run length
encoding, huffman coding, discrete cosine transform, vector
quantization, fuzzy transform. This gives a brief idea on improved
fuzzy technique to reduce noise in compressing image. There are
so many techniques for compression but in this only present the
techniques of improved fuzzy method to reduce noise and
compressed the image by using edge detection. The main idea
behind applying this is we have to preserve the well significant
edges as Jpeg is the popular standard but at low bit rate Jpeg
exhibits blocking artifacts means noisy effects that affect the
visual image quality so to produce high visual quality image at
low bit rate ,the algorithm is efficient and simple. The proposed
algorithm consists of three steps. First, image is preprocessed
using competitive fuzzy edge detection. Second, based on edge
information image is compressed and decompressed using
improved fuzzy transform. Third, reconstructed image is post
processed using hybrid median filter for artifact reduction.
Analysis proves the superiority of proposed algorithm. The results
of different number of coefficients are compared with the value of
PSNR, MSE of algorithm. After comparison of techniques it is
found to be efficient for visualization.
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.