Intrinsic Light Field Images
Elena Garces, Jose I. Echevarria, Wen Zhang, Hongzhi Wu, Kun Zhou,, Diego Gutierrez

TL;DR
This paper introduces a novel method for decomposing 4D light field images into intrinsic shading and albedo components, addressing the challenges of higher dimensionality and coherence in previous approaches.
Contribution
It presents a new joint optimization algorithm for 4D light fields that enforces angular coherence and extends Retinex theory for efficiency.
Findings
Provides 4D intrinsic decompositions difficult for previous methods
Achieves better coherence across angular dimensions
Outperforms existing intrinsic image/video decomposition techniques
Abstract
We present a method to automatically decompose a light field into its intrinsic shading and albedo components. Contrary to previous work targeted to 2D single images and videos, a light field is a 4D structure that captures non-integrated incoming radiance over a discrete angular domain. This higher dimensionality of the problem renders previous state-of-the-art algorithms impractical either due to their cost of processing a single 2D slice, or their inability to enforce proper coherence in additional dimensions. We propose a new decomposition algorithm that jointly optimizes the whole light field data for proper angular coherence. For efficiency, we extend Retinex theory, working on the gradient domain, where new albedo and occlusion terms are introduced. Results show our method provides 4D intrinsic decompositions difficult to achieve with previous state-of-the-art algorithms. We…
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