Work place: Dept of CSE, JNTU Hyderabad, Telangana
Research Interests: Image Processing, Image Manipulation, Image Compression, Pattern Recognition
S.Vijaya Kumar Received the B.Tech (CSE) degree from KSRM College of Engineering in 2004. He received the M.Tech (CS) degree from RGMCET Nandyal in 2007. At present pursuing Ph.D., in Digital Image Processing from JNTU Hyderabad and working as Assistant Professor in the department of IT at RGMCET, Nandyal. He has got 10 years of teaching experience. His research interest includes Image Processing, Pattern Recognition. He has 14 research papers in various national and international journal and conferences. He has 12 seminars and workshops. He is member of various professional societies like IEEE, IAENG, IACSIT and CSI
DOI: https://doi.org/10.5815/ijigsp.2018.03.05, Pub. Date: 8 Mar. 2018
Impulse noise is the prime factor which reduces the quality of the digital image and it erases the important details of the images. De-noising is an indispensable task to restore the image features from the corrupted low- quality images and improve the perceptual quality of images. Several techniques are used for image quality enhancement and image restoration. In this work, an image de-noising scheme is developed to detect and correct the impulse noise from the image by using fuzzy entropy. The proposed algorithm is designed in two phases, such as noise detection phase, and correction phase. In the noise detection phase, the fuzzy entropy of pixels in a window of interest (WoI) is computed to detect whether the pixel is noisy or not. The Fuzzy entropy of pixel greater than specified alpha cut value will be considered as noise pixel and submitted to correction phase. In the correction phase noise pixel value is replaced with a fuzzy weighted mean of the un-corrupted pixels in the WoI. The proposed Fuzzy entropy based impulse noise detection and correction method are implemented using MATLAB. The experimentation has been carried out on different standard images and the analysis is performed by comparing the performance of the proposed scheme with that of the existing methods such as DBA, MDBUTMF, AMF, NAFSM, BDND, and CM , using PSNR, SSIM, and NAE as metric parameters. The proposed method will give good results compared to state of the art methods in image restoration.[...] Read more.
Subscribe to receive issue release notifications and newsletters from MECS Press journals