This paper is published in Volume-4, Issue-3, 2018
Area
Computer Engineering
Author
Mitali Wadhwa, Rajiv Sharma
Org/Univ
Shree Baba Mastnath Engineering College, Rohtak, Haryana, India
Keywords
Fuzzy system, Processing algorithm, Digital images
Citations
IEEE
Mitali Wadhwa, Rajiv Sharma. Fuzzy logics and soft computing techniques for noise reduction, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Mitali Wadhwa, Rajiv Sharma (2018). Fuzzy logics and soft computing techniques for noise reduction. International Journal of Advance Research, Ideas and Innovations in Technology, 4(3) www.IJARIIT.com.
MLA
Mitali Wadhwa, Rajiv Sharma. "Fuzzy logics and soft computing techniques for noise reduction." International Journal of Advance Research, Ideas and Innovations in Technology 4.3 (2018). www.IJARIIT.com.
Mitali Wadhwa, Rajiv Sharma. Fuzzy logics and soft computing techniques for noise reduction, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Mitali Wadhwa, Rajiv Sharma (2018). Fuzzy logics and soft computing techniques for noise reduction. International Journal of Advance Research, Ideas and Innovations in Technology, 4(3) www.IJARIIT.com.
MLA
Mitali Wadhwa, Rajiv Sharma. "Fuzzy logics and soft computing techniques for noise reduction." International Journal of Advance Research, Ideas and Innovations in Technology 4.3 (2018). www.IJARIIT.com.
Abstract
The aim of noise reduction is to extract the desired signal from its noise-corrupted version, using the proposed neuro-fuzzy system (NFS) as an adaptive filter. Noise reduction is the process of removing noise from a signal. All recording devices, both analog and digital, have traits that make them susceptible to noise. Noise can be random or white noise with no coherence, or coherent noise introduced by the device's mechanism or processing algorithms. Digital images are mostly corrupted by mixed noise from several sources. It is a challenging problem to remove mixed noise in color images. Generally, some image denoising filters can reduce either additive or impulse noise, but it fails to remove both impulsive noise and additive noise.
