Name
Abstract | ||
|---|---|---|
Complementary metal-oxide-semiconductor (CMOS) image sensors can cause noise in images collected or transmitted in unfavorable environments, especially low-illumination scenarios. Numerous approaches have been developed to solve the problem of image noise removal. However, producing natural and high-quality denoised images remains a crucial challenge. To meet this challenge, we introduce a novel approach for image denoising with the following three main contributions. First, we devise a deep image prior-based module that can produce a noise-reduced image as well as a contrast-enhanced denoised one from a noisy input image. Second, the produced images are passed through a proposed image fusion (IF) module based on Laplacian pyramid decomposition to combine them and prevent noise amplification and color shift. Finally, we introduce a progressive refinement (PR) module, which adopts the summed-area tables to take advantage of spatially correlated information for edge and image quality enhancement. Qualitative and quantitative evaluations demonstrate the efficiency, superiority, and robustness of our proposed method. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.3390/s21165391 | SENSORS |
Keywords | DocType | Volume |
noise removal, deep image prior, edge enhancement, contrast enhancement | Journal | 21 |
Issue | ISSN | Citations |
16 | 1424-8220 | 0 |
PageRank | References | Authors |
0.34 | 0 | 9 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shih-Chia Huang | 1 | 1 | 1.39 |
| Quoc-Viet Hoang | 2 | 0 | 0.34 |
| Trung-Hieu Le | 3 | 2 | 1.55 |
| Yan-Tsung Peng | 4 | 0 | 0.68 |
| Ching-Chun Huang | 5 | 7 | 4.91 |
| Cheng Zhang | 6 | 0 | 0.34 |
| Benjamin C M Fung | 7 | 0 | 0.34 |
| Kai-Han Cheng | 8 | 0 | 0.34 |
| Sha-Wo Huang | 9 | 0 | 0.34 |