By: Promila Singhal, Tarun Dhiman, and Ishta Rani
With the rapid advancement of today’s information technology, the analysis of digital images has endured rapid evolution in technology and is frequently utilized in everyday situations and enterprises. There are specific problems in the transmission process. Images are influenced by the compression of data and communication. In color image processing, a variety of well-established approaches to suppressing noise are offered. The variety of noise corrupting the image determines the nature of the reduction in noise challenge. There have been various linear and nonlinear filtering techniques proposed in the subject of noisy visuals reduction. Noise caused by impulses cannot be effectively eliminated by linear filters because of their propensity to blur an image’s edges. Nonlinear filters, on the other hand, perform well with impulse noise. In recent years, a number of nonlinear filters based on fuzzy and conventional approaches have been invented. In this paper the denoise adaptive median filter (DAMF) is offered for reducing impulse noise in this research. It includes two stages for filter design. The initial step is the recognition of damaged pixels, then restoring. A fuzzy inference rule membership functions for detection and a traditional median filter for reconstruction.
Keywords: Image Denoising, Filters, denoise adaptive median filter (DAMF), Nonlinear filter, digital image, image processing, Gaussian noise
Citation:
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