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We present a novel method for matching ground-based query images to a georeferenced LIDAR 3D dataset acquired from an airborne platform in urban environments. We are addressing two main technical challenges: (i) different modalities between the query and the reference data (electro-optical vs. LIDAR) that impose unique challenges to the matching problem; (ii) very different viewing directions from...
This paper reconstructs multivariate functions from scattered data by a new multiscale technique. The reconstruction uses support vector regression model by positive definite reproducing kernels in Hilbert spaces. But it adopts techniques from wavelet theory and shift-invariant spaces to construct a new class of kernels as multiscale superpositions of shifts and scales of a single compactly supported...
Super-resolution image reconstruction has been one of the most active research areas in recent years. Based on the theory of statistical learning, Mercer condition and the wavelet frame, this paper proposes a new multiscale wavelet support vector regression model (MWSVR) to reconstruction super-resolution image from low-resolution image and missing data image. The SVM essence is kernel method and...
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