Quantization artifact detection and removal in images

In this age of rapid development of science and technology, people get information in various ways, from computers, from mobile phones, from books. Among them, image as an important carrier of information transmission. Its importance in people's life is self-evident. Image distortion caused by...

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Bibliographic Details
Main Author: Song, Xinyi
Other Authors: Tay Wee Peng
Format: Thesis-Master by Coursework
Language:English
Published: Nanyang Technological University 2023
Subjects:
Online Access:https://hdl.handle.net/10356/168901
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Institution: Nanyang Technological University
Language: English
Description
Summary:In this age of rapid development of science and technology, people get information in various ways, from computers, from mobile phones, from books. Among them, image as an important carrier of information transmission. Its importance in people's life is self-evident. Image distortion caused by image folding is a new research field. After being repaired by the Markov random field method, the image still has distortion. This dissertation mainly studies deep learning methods and traditional image processing methods to further solve image distortion, which involves relevant theoretical knowledge in the field of image super resolution, including convolutional neural networks, residual networks, dense networks and various classical image super resolution networks. In this dissertation, the VDSR model is modified and a good result is obtained.