IEEE Trans Pattern Anal Mach Intell - A Closed-Form Solution to Retinex with Nonlocal Texture Constraints.

Tópicos

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Resumo

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.

Resumo Limpo

propos method intrins imag decomposit base retinex theori textur analysi previous method approach problem analyz local gradient properti techniqu addit identifi distant pixel reflect textur analysi use nonloc reflect constraint signific reduc ambigu decomposit formul decomposit problem minim quadrat function incorpor retinex constraint nonloc textur constraint optim can solv close form standard conjug gradient algorithm extens experiment comparison previous techniqu valid method term decomposit accuraci runtim effici

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