Open AccessDenoising of Images Using Autoencoder
Author(s) -
Shreya Shrikant Naik,
. Sowmya,
N K Preethika
Publication year - 2020
Publication title -
international journal of scientific research in computer science, engineering and information technology
Language(s) - English
Resource type - Journals
ISSN - 2456-3307
DOI - 10.32628/cseit2063122
Subject(s) - computer science , artificial intelligence , computer vision , image restoration , autoencoder , noise reduction , noise (video) , process (computing) , image processing , image (mathematics) , image quality , image compression , deep learning , operating system
Image is the object that stores and reflects visual perception. Images are also important information carriers today. Acquisition channel and artificial editing are the two main ways that corrupt observed images. The goal of image restoration technique is to restore the original image from a noisy observation of it which is aiming to reconstruct a high quality image from its low quality observation has many important applications, like low-level image processing, medical imaging, remote sensing, surveillance, etc. Image denoising is common image restoration problems that are useful by many industrial and scientific applications. The application classifies images based on single image selected from user. The noise from the corrupted image is removed and original clear image is obtained. In our project we are making use of Auto-encoder. Auto-encoder do not need much data pre-processing and it is an end to end training process which helps to remove the noise present in some pictures using some data compression algorithms.