Restore image by removing artifacts superimposed in an unknown manner
Restore image by removing artifacts superimposed in an unknown manner
Blind Image Decomposition
arXiv paper abstract https://arxiv.org/abs/2108.11364v1
arXiv PDF paper https://arxiv.org/pdf/2108.11364v1.pdf
... Blind Image Decomposition (BID), which requires separating a superimposed image into constituent underlying images in a blind setting, that is, both the source components involved in mixing as well as the mixing mechanism are unknown.
For example, rain may consist of multiple components, such as rain streaks, raindrops, snow, and haze.
Rainy images can be treated as an arbitrary combination of these components, some of them or all of them.
How to decompose superimposed images, like rainy images, into distinct source components is a crucial step towards real-world vision systems.
... we construct three benchmark datasets, including mixed image decomposition across multiple domains, real-scenario deraining, and joint shadow/reflection/watermark removal.
... propose a simple yet general Blind Image Decomposition Network (BIDeN) to serve as a strong baseline for future work.
... demonstrate the tenability of our benchmarks and the effectiveness of BIDeN. ...
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