Geometry based three-dimensional image processing method for electronic cluster eye
Sidong Wu, Gexiang Zhang, Ming Qiao Zhu, Tao Jiang, Ferrante Neri · Integrated Computer-Aided Engineering · 2018
In recent years, much attention has been paid to the electronic cluster eye (eCley), a new type of artificial compound eyes, because of its small size, wide field of view (FOV) and sensitivity to motion objects. An eCley is composed of a certain number of optical channels organized as an array. Eac h optical channel spans a small and fixed field of view (FOV). To obtain a complete image with a full FOV, the images from all the optical channels are required to be fused together. The parallax from unparallel neighboring optical channels in eCley may lead to reconstructed image blurring and incorrectly estimated depth. To solve this problem, this paper proposes a geometry based three-dimensional image processing method (G3D) for eCley to obtain a complete focused image and dense depth map. In G3D, we derive the geometry relationship of optical channels in eCley to obtain the mathematical relation between the parallax and depth among unparallel neighboring optical channels. Based on the geometry relationship, all of the optical channels are used to estimate the depth map and reconstruct a focused image. Subsequently, by using an edge-aware interpolation method, we can further gain a sharply focused image and a depth map. The effectiveness of the proposed method is verified by the experimental results.