Colour Image Noise Removal using Convolution Neural Network
Sujatha Canavoy Narahari, K. Haripriya, M. Srinath, Ch. Jasmitha · 2024
Image noise removal is an essential task in image processing with applications in different domains such as photography, computer vision, and medical imaging. The presence of noise can degrade the quality of images and affect subsequent processing tasks, such as object recognition and image analysis. Hence, removing noise from images are essential to improve the quality and increase the accuracy of these applications. Convolutional Neural Networks (CNN) have upheld encouraging performance in image denoising challenges in recent years. CNN is capable to preserve connections between an image's pixels. CNN has exclusive layer architecture which is preferable for processing image data. CNNs are enforced in an autoencoder framework. In the autoencoder framework it consists of encoder and decoder sections. Each images sample in the input is an image including noise, and every image sample in the output is the same image without noise. After applying the trained model to a noisy image, a clear image can be produced