Layered perceptual representation for shadow vision: From detection to removal

Abstract

On the research of shadow essence and visual scheme, we propose a single image shadow removal method based on certain layered perceptual representation models with the flowchart from shadow detection to shadow removal. Firstly, a modified intersecting cortical model, the typically useful image factorization technique, is applied to extract umbra and penumbra masks. Then, under the energy minimization framework, scale factors for umbra are computed. Furthermore, transparency-coupled atmospheric transfer function is introduced for penumbra compensation by pixel-by-pixel transparency estimation. For aerial images, experimental results illustrate that shadow regions are matted well, and the proposed method yields vivid shadow-free images with smooth boundaries.