Stereo vision for facet type cameras

In the last decade, scientists have put forth many artificial compound eye systems, inspired by the compound eyes of all kinds of insects. These systems, employing multi-aperture optical systems instead of single-aperture optical systems, provide many specific characteristics, such as small volume, light weight, large view, and high sensitivity. Electronic cluster eye (eCley) is a state-of-the-art artificial superposition compound eye with super resolution, which is inspired by a wasp parasite called the Xenos Peckii. Thanks to the inherent characteristics of eCley, it has successfully been applied to aspects of medical inspection, personal identification, bank safety, robot navigation, and missile guidance. However, all these applications only involve a two-dimensional image space, i.e., no three-dimensional (3D) information is provided. Conceiving of the ability of detecting 3D space information using eCley, the performances of 3D reconstruction, object position, and distance measurement will be obtained easily from the single eCley rather than requiring extra depth information devices. In practice, there is a big challenge to implementing 3D space information detection in the minimized eCley, although structures similar to stereo vision exist in each pair of adjacent channels. In the case of an imaging channel with short focal length and low resolution, the determination of the depth information not only is an ill-posed problem but also varies in the range of one pixel from quite near distance (≥86 mm), which restricts the applicability of popular stereo matching algorithms to eCley. Taking aim at this limitation, and with the goal of satisfying the real demands of applications in eCley, this thesis mainly studies a novel method of subpixel stereo vision for eCley. This method utilizes the significant property of object edges still retained in eCley, i.e., the transitional areas of edges contain rich information including the depths or distances of objects, to determine subpixel distances of the corresponding pixel pairs in the adjacent channels, to further obtain the objects' depth information by employing the triangle relationship. In the whole thesis, I mainly deduce the mathematical model of stereo vision in eCley theoretically based on its special structure, discuss the optical correction and geometric calibration that are essential to high precision measurement, study the implementation of methods of the subpixel baselines for each pixel pair based on intensity information and gradient information in transitional areas, and eventually implement real-time subpixel distance measurement for objects through these edge features. To verify the various methods adopted, and to analyze the precision of these methods, I employ an artificial synthetical stereo channel image and a large number of real images captured in diverse scenes in my experiments. The results from either a process or the whole method prove that the proposed methods efficiently implement stereo vision in eCley and the measurement of the subpixel distance of stereo pixel pairs. Through a sensitivity analysis with respect to illumination, object distances, and pixel positions, I verify that the proposed method also performs robustly in many scenes. This stereo vision method extends the ability of perceiving 3D information in eCley, and makes it applicable to more comprehensive fields such as 3D object position, distance measurement, and 3D reconstruction.