Digital Image

ProcessingRemoval of Salt and Pepper Using Fuzzy Switching average Filter
ARSLAN IQBALYASIR AZIZILYAS MADNI
Department of data processor Engineering, Department of Computer Engineering,Department of Computer Engineering,
University Of Engineering & engine roomUniversity Of Engineering & TechnologyUniversity Of Engineering & Technology
Lahore, PakistanLahore, PakistanLahore, Pakistan


Abstractâ€" This paper presents a unexampled dazed median filter (FSM) employing fuzzy technique removing lust hoo-ha in digital substitution classs. The proposed technique is able to key and run into impulse noise in digital learns temporary hookup preserving image details and textures. A key concept of fuzzy switching median (FSM) filter helps to find and fill impulse noise associated with an image by checking the relative pixel values.

Keywordsâ€" thirst Noise, Salt and Pepper Noise, Fuzzy Median Filter, Image Processing.
Introduction
SALT-AND-PEPPER noise is a special case of impulse noise, where a authoritative percentage of individual pixels in digital image atomic number 18 randomly digitized into two extreme intensities. The contamination of salt-and-pepper in digital image caused by external disturbance in image acquisition, noisy sensor and channel transmission errors.



It is important to remove salt-and-pepper noise contained in the digital images by preserving the image integrity.
* To remove salt-and-pepper noise is imperative before subsequent image touch on tasks such as segmentation or edge detecting is carried out. Occurrence of salt and-pepper noise can severely terms the information or data embedded in the digital image. The easiest ways to remove salt-and-pepper noise is by windowing the noisy image with a conventional median filter [1]. The conventional median filter restores each pixel with the median pixel in the filtering window regardless whether it is a noise or noise-free pixel that makes the filtered image blurred.
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