Auto Encoders and Decoders Techniques of Convolutional Neural Network Approach for Image Denoising In Deep Learning

Abstract

Image Denaoising (I.D) is the process of eliminating noise from the Images. The noise present in the images may be caused by various
conditions which are practically hard to deal with. The procedure of eliminating noise from images given is recognized as image denoising.
The noise in the photos might be generated by a variety of factors that are difficult to deal with. In order to process images for purposes such
as object segmentation, detection, and tracking, it became a critical job to eliminate the noise from an image and to restore a high resolution
image. The image is first given a layer of noise ranging from 1% to 10%, and then the CNN model is used to denoise it. The denoised image
is next subjected to qualitative and quantitative analysis. The encoder and decoder layers of the CNN model are responsible for denoising the
image. This strategy focuses picture denoising using the Auto encoders and decoders of convolutional neural network (CNN) model in deep
learning, but the median filter tends to remove image information. The results of the analysis and experiment show that the CNN model is
more effective than other traditional/standard image filtering techniques at removing noise and restoring image details and data.