Effective shadow removal via multi-scale image decomposition
Autor: | Qingan Yan, Xiaolong Zhang, Chunxia Xiao, Yao Zhu, Ling Zhang |
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Rok vydání: | 2019 |
Předmět: |
Computer science
business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Process (computing) Boundary (topology) 020207 software engineering Image processing 02 engineering and technology Computer Graphics and Computer-Aided Design GeneralLiterature_MISCELLANEOUS Image (mathematics) Computer graphics Shadow 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Computer vision Computer Vision and Pattern Recognition Artificial intelligence Scale (map) business Software Smoothing ComputingMethodologies_COMPUTERGRAPHICS |
Zdroj: | The Visual Computer. 35:1091-1104 |
ISSN: | 1432-2315 0178-2789 |
Popis: | Shadow removal is a fundamental and challenging problem in image processing field. Current approaches can only process shadows with simple scenes. For complex texture and illumination, the performance is less impressive. In this paper, we propose a novel shadow removal algorithm based on multi-scale image decomposition, which can recover the illumination for complex shadows with inconsistent illumination and different surface materials. Independent of shadow detection, our algorithm only requires a rough boundary distinguishing shadow regions from non-shadow regions. It first performs a multi-scale decomposition for the input image based on an illumination-sensitive smoothing process and then removes shadows in the basic layer using a local-to-global optimization strategy, which fuses all local shadow-free results in a global manner. Finally, we recover the texture details for the shadow-free basic layer and obtain the final shadow-free image. We validate the performance of the proposed method under various lighting and texture conditions and show consistent illumination between shadow and surrounding regions in the shadow removal results. |
Databáze: | OpenAIRE |
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