Noise Removal from Images Using Adaptive Neuro/Network-Fuzzy Interface Systems

Autor: Krishna Prasad Pulipaka, K. Sathish Kumar, K. Geethali Apoorva, Rohith Rao, K. Radha Krishna
Rok vydání: 2022
Zdroj: International Journal of Engineering and Applied Technologies. 22:15-32
ISSN: 2672-8753
DOI: 10.56431/p-t615v7
Popis: Any Information signal is best desirable without any external noise/ disturbances. Noise in any signal is the undesirable quantity present which deteriorates the signal's quality, thus compromising the information. Any signal, be it an image signal (2-D) or else a video signal (3-D) in the field of communication, if not always but most number of times prone to noise. In this paper, we would be dealing with removing types of noise on an image, using various filter techniques such as vector median filter, vector directional filter. Using the image processing tools in MATLAB, we could achieve this quite effortlessly. Looking at the prior approaches and keeping those factors in understanding, this paper would intend to path a more thoughtful way to bifurcate the image from its noise using the techniques of the neural networks. With thorough scrutiny and understanding of filters, this paper ensemble the performance of filters, through which we would be applying the most suitable filter out of the lot with the neural networks.
Databáze: OpenAIRE