A study of video denoising based on deep learning
Video denoising is a fundamental low-level vision task which means videos corrupted by noise are restored and high-quality videos are obtained. With deep learning techniques applied in the computer vision area, models based on deep neural network began to replace traditional algorithms. In this d...
Main Author: | Zou, Dejian |
---|---|
Other Authors: | Wen Bihan |
Format: | Thesis-Master by Coursework |
Language: | English |
Published: |
Nanyang Technological University
2024
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/180018 |
Similar Items
-
Impact of Traditional and Embedded Image Denoising on CNN-Based Deep Learning
by: Roopdeep Kaur, et al.
Published: (2023-10-01) -
Deep residual learning for denoising Monte Carlo renderings
by: Kin-Ming Wong, et al.
Published: (2019-05-01) -
Comparison of deep learning-based denoising methods in cardiac SPECT
by: Antti Sohlberg, et al.
Published: (2023-02-01) -
Concurrent Video Denoising and Deblurring for Dynamic Scenes
by: Efklidis Katsaros, et al.
Published: (2021-01-01) -
SlantletTransformbased VideoDenoising
by: Baghdad Science Journal
Published: (2011-06-01)