Fully automatic DOM generation method based on optical flow field dense image matching

Automatic Digital Orthophoto Map(DOM)generation plays an important role in many downstream works such as land use and cover detection,urban planning,and disaster assessment.Existing DOM generation methods can generate promising results but always need ground object filtered DEM generation before otho-rectification;this can consume much time and produce building facade contained results.To address this problem,a pixel-by-pixel digital differential rectification-based automatic DOM generation method is proposed in this paper.Firstly,3D point clouds with texture are generated by dense image matching based on an optical flow field for a stereo pair of images,respectively.Then,the grayscale of the digital differential rectification image is extracted directly from the point clouds element by element according to the nearest neighbor method for matched points.Subsequently,the elevation is repaired grid-by-grid using the multi-layer Locally Refined B-spline(LR-B)interpolation method with triangular mesh constraint for the point clouds void area,and the grayscale is obtained by the indirect scheme of digital differential rectification to generate the pixel-by-pixel digital differentially rectified image of a single image slice.Finally,a seamline network is automatically searched using a disparity map optimization algorithm,and DOM is smartly mosaicked.The qualitative and quantitative experimental results on three datasets were produced and evaluated,which confirmed the feasibility of the proposed method,and the DOM accuracy can reach 1 Ground Sample Distance(GSD)level.The comparison experiment with the state-of-the-art commercial softwares showed that the proposed method generated DOM has a better visual effect on building boundaries and roof completeness with comparable accuracy and computational efficiency.

Robust optical flow estimation based on brightness correction fields

Optical flow estimation is still an important task in computer vision with many interesting applications.However,the results obtained by most of the optical flow techniques are affected by motion discontinuities or illumination changes.In this paper,we introduce a brightness correction field combined with a gradient constancy constraint to reduce the sensibility to brightness changes between images to be estimated.The advantage of this brightness correction field is its simplicity in terms of computational complexity and implementation.By analyzing the deficiencies of the traditional total variation regularization term in weakly textured areas,we also adopt a structure-adaptive regularization based on the robust Huber norm to preserve motion discontinuities.Finally,the proposed energy functional isminimized by solving its corresponding Euler-Lagrange equation in a more effective multi-resolution scheme,which integrates the twice downsampling strategy with a support-weight median filter.Numerous experiments show that our method is more effective and produces more accurate results for optical flow estimation.

Redistributing the energy flow of tightly focused ellipticity-variant vector optical fields

The redistribution of the energy flow of tightly focused ellipticity-variant vector optical fields is presented.We theoretically design and experimentally generate this kind of ellipticity-variant vector optical field, and further explore the redistribution of the energy flow in the focal plane by designing different phase masks including fanlike phase masks and vortex phase masks on them. The flexibly controlled transverse energy flow rings of the tightly focused ellipticity-variant vector optical fields with and without phase masks can be used to transport multiple absorptive particles along certain paths, which may be widely applied in optical trapping and manipulation.