@article{(Open Science Index):https://publications.waset.org/pdf/11097,
	  title     = {Image Restoration in Non-Linear Filtering Domain using MDB approach},
	  author    = {S. K. Satpathy and  S. Panda and  K. K. Nagwanshi and  C. Ardil},
	  country	= {},
	  institution	= {},
	  abstract     = {This paper proposes a new technique based on nonlinear Minmax Detector Based (MDB) filter for image restoration. The aim of image enhancement is to reconstruct the true image from the corrupted image. The process of image acquisition frequently leads to degradation and the quality of the digitized image becomes inferior to the original image. Image degradation can be due to the addition of different types of noise in the original image. Image noise can be modeled of many types and impulse noise is one of them. Impulse noise generates pixels with gray value not consistent with their local neighborhood. It appears as a sprinkle of both light and dark or only light spots in the image. Filtering is a technique for enhancing the image. Linear filter is the filtering in which the value of an output pixel is a linear combination of neighborhood values, which can produce blur in the image. Thus a variety of smoothing techniques have been developed that are non linear. Median filter is the one of the most popular non-linear filter. When considering a small neighborhood it is highly efficient but for large window and in case of high noise it gives rise to more blurring to image. The Centre Weighted Mean (CWM) filter has got a better average performance over the median filter. However the original pixel corrupted and noise reduction is substantial under high noise condition. Hence this technique has also blurring affect on the image. To illustrate the superiority of the proposed approach, the proposed new scheme has been simulated along with the standard ones and various restored performance measures have been compared.
},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {7},
	  number    = {2},
	  year      = {2013},
	  pages     = {328 - 332},
	  ee        = {https://publications.waset.org/pdf/11097},
	  url   	= {https://publications.waset.org/vol/74},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 74, 2013},
	}