Issue No. 07 - July (2012 vol. 34)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TPAMI.2012.77
Qi Zhao , National University of Singapore, Singapore
Ping Tan , National University of Singapore, Singapore
Qiang Dai , Jilin University, Jilin
Li Shen , Institute for Infocomm Research, Singapore
Enhua Wu , Chinese Academy of Sciences, Beijing
Stephen Lin , Microsoft Research Asia, Beijing
We propose a method for intrinsic image decomposition based on retinex theory and texture analysis. While most previous methods approach this problem by analyzing local gradient properties, our technique additionally identifies distant pixels with the same reflectance through texture analysis, and uses these nonlocal reflectance constraints to significantly reduce ambiguity in decomposition. We formulate the decomposition problem as the minimization of a quadratic function which incorporates both the retinex constraint and our nonlocal texture constraint. This optimization can be solved in closed form with the standard conjugate gradient algorithm. Extensive experimentation with comparisons to previous techniques validate our method in terms of both decomposition accuracy and runtime efficiency.
Intrinsic images, retinex, nonlocal constraint, texture.
S. Lin, E. Wu, L. Shen, Q. Dai, Q. Zhao and P. Tan, "A Closed-Form Solution to Retinex with Nonlocal Texture Constraints," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 34, no. , pp. 1437-1444, 2012.