A Variational Framework for Retinex
International Journal of Computer Vision
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Detecting Moving Shadows: Algorithms and Evaluation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shadow detection for moving objects based on texture analysis
Pattern Recognition
Learning and Removing Cast Shadows through a Multidistribution Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Segmentation of soft shadows based on a daylight- and penumbra model
MIRAGE'07 Proceedings of the 3rd international conference on Computer vision/computer graphics collaboration techniques
A novel shadow detection algorithm for real time visual surveillance applications
ICIAR'06 Proceedings of the Third international conference on Image Analysis and Recognition - Volume Part II
Detecting moving objects, ghosts, and shadows in video streams
IEEE Transactions on Pattern Analysis and Machine Intelligence
A multiscale retinex for bridging the gap between color images and the human observation of scenes
IEEE Transactions on Image Processing
A new approach for lighting effect rendering
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part III
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Shadows are physical phenomena observed in most natural scenes. They can cause many problems in computer vision performance. The paper addresses the problem of shadow detection and removal from solo image of natural scenes. Our method is based on Retinex theory which is an image enhancement and illumination compensation model of the lightness and color perception of human vision. The approach proposed here does not use any special prior knowledge and assumptions. The shadow extraction algorithm originates from a simple idea that the human-vision-based Retinex has the natural ability to enhance the shadow region of an image no matter it is penumbrae or umbrae. The penumbrae and umbrae regions will be highlighted if we compare the Retinex-enhanced images with original images. Then through adding smooth light forcibly to shadow edges and introducing shadow edge masks, we reduce the effects of shadow edges in the Retinex enhancement processing. Experiment results validate the approach.