No-Reference Quality Assessment of Deblurred Images Based on Natural Scene Statistics
Blurring is one of the most common distortions in digital images. In the past decade, extensive image deblurring algorithms have been proposed to restore a latent clean image from its blurred version. However, very little work has been dedicated to the quality assessment of deblurred images, which m...
Main Authors: | Li, Leida, Yan, Ya, Lu, Zhaolin, Wu, Jinjian, Gu, Ke, Wang, Shiqi |
---|---|
Other Authors: | School of Computer Science and Engineering |
Format: | Journal Article |
Language: | English |
Published: |
2018
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/87058 http://hdl.handle.net/10220/44298 |
Similar Items
-
Swin-Diff: a single defocus image deblurring network based on diffusion model
by: Hanyan Liang, et al.
Published: (2025-02-01) -
Lightweight defocus deblurring network for curved-tunnel line scanning using wide-angle lenses
by: Shaojie Qin, et al.
Published: (2025-02-01) -
Single Image Defocus Deblurring Based on Structural Information Enhancement
by: Guangming Feng, et al.
Published: (2024-01-01) -
A Note on the Convergence of Multigrid Methods for the Riesz–Space Equation and an Application to Image Deblurring
by: Danyal Ahmad, et al.
Published: (2024-06-01) -
Image deblurring method for satellite platform caused by jitter
by: Xiao-lin SONG, et al.
Published: (2017-10-01)