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All-In-Focus Synthetic Aperture Imaging
Tao Yang1, Yanning Zhang1, Jingyi Yu2, Jing Li3, Wenguang Ma1, Xiaomin Tong1, Rui Yu4, and Lingyan Ran1
1SAIIP, School of Computer Science, Northwestern Polytechnical University, China
yangtaonwpu@163.com
ynzhangnwpu@gmail.com
2Deptartment of CIS, University of Delaware, USA
yu@eecis.udel.edu
3School of Telecommunications Engineering, Xidian University, China
4Deptartment of Computer Science, University College London, UK
Abstract. Heavy occlusions in cluttered scenes impose significant challenges to many computer vision applications. Recent light field imaging systems provide new see-through capabilities through synthetic aperture imaging (SAI) to overcome the occlusion problem. Existing synthetic aperture imaging methods, however, emulate focusing at a specific depth layer but is incapable of producing an all-in-focus see-through image. Alternative in-painting algorithms can generate visually plausible results but can not guarantee the correctness of the result. In this paper, we present a novel depth free all-in-focus SAI technique based on light-field visibility analysis. Specifically, we partition the scene into multiple visibility layers to directly deal with layer-wise occlusion and apply an optimization framework to propagate the visibility information between multiple layers. On each layer, visibility and optimal focus depth estimation is formulated as a multiple label energy minimization problem. The energy integrates the visibility mask from previous layers, multi-view intensity consistency, and depth smoothness constraint. We compare our method with the state-of-the-art solutions. Extensive experimental results with qualitative and quantitative analysis demonstrate the effectiveness and superiority of our approach.
Keywords: occluded object imaging, all-in-focus synthetic aperture imaging, multiple layer visibility propagation
LNCS 8694, p. 1 ff.
lncs@springer.com
© Springer International Publishing Switzerland 2014