In free space optical communication, the transmission characteristics through atmospheric channel have important effect on system performance, for example, atmospheric turbulence can cause fluctuations in both the intensity and the phase of the received light signal. The existing system mostly uses intensity modulation and direct detection(IM/DD) because of low complexity and cost, despite atmospheric turbulence can significantly impair link performance and induce a string of error bits. In order to mitigate turbulence effect, coding techniques can be adopted. For a long string of error induced by turbulence units, interlaced code changes the abrupt error into absolute error, thus it can be easily corrected. We analyze the impact of interlaced code on the performance of FSO system whose signal passes through the turbulent atmosphere. Simulations are presented to verify the performance improvement achieved using coding for free space optical communication through atmospheric turbulence channel.
In this paper, we introduce the linear constrains of circular points on camera's intrinsic parameters firstly and propose the uniqueness condition of the solutions, then we elaborate a novel linear approach for computing the images of circular points as well as camera calibration from images of two unparallel coplanar rectangles in space. The main advantage of our technique lies in that neither the metric measurement of the rectangles nor the correspondences between images are required. Extensive simulations and experiments with real images, as well as the comparative study with Zhang's method, validate our algorithms and demonstrate that the proposed technique is of high precision and strong robustness.
Affine reconstruction is the most difficult and crucial step in 3D reconstruction from image space to the Euclidean space. Recent research indicates that it is impossible to realize the affine reconstruction from a perspective image pairs captured by a translating camera with varying intrinsic parameters if no geometric information of the scene is available. Therefore, it is indispensable to provide some additional information for affine reconstruction from a pair of images. In this paper, we propose that if one plane and a pair of parallel lines are presented in the scene, the affine reconstruction can be done linearly from two images taken by a translating camera. We also point out that if a pair of parallel planes is presented in the scene, the affine reconstruction can also be done linearly from an image pair taken by a translating camera, and if a pair of parallel planes and a pair of parallel lines are presented in the scene, the affine reconstruction can be done linearly from two general views. Extensive simulations and experiments with real images validate our algorithm. The result ofthis paper seems ofboth academic and practical significance in 3D computer vision.