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In this paper, we proposed a novel algorithm of automatic image structure completion. Different from traditional image completion algorithms directly copying patches from the unknown region to the damaged part, our completion approach first reconstructs the geometry structures in the damaged region with edges inferred by Constrained Delaunay Triangulation (CDT), and select correct edges through a...
This paper proposes a context-constrained hallucination approach for image super-resolution. Through building a training set of high-resolution/low-resolution image segment pairs, the high-resolution pixel is hallucinated from its texturally similar segments which are retrieved from the training set by texture similarity. Given the discrete hallucinated examples, a continuous energy function is designed...
We present a robust algorithm for spatial recovery of missing region in images. The algorithm consists of two stages: sparse modeling and patch based refinement. We note that a model based image recovery might not be able to reconstruct the richness or details in a signal unless the signal truly fits that model. We show that the reconstruction using a sparse model provides enough information about...
In this paper a context based super-resolution (SR) image reconstruction method is proposed. The proposed maximum a-posteriori (MAP) based estimator identifies local gradients and textures for selecting the optimal SR method for the region of interest. Texture segmentation and gradient map estimation are done prior to the reconstruction stage. Gradient direction is used for optimal noise reduction...
Accurate localization of landmarks in the vicinity of a robot is a first step towards solving the SLAM problem. In this work, we propose algorithms to accurately estimate the 3D location of the landmarks from the robot only from a single image taken from its on board camera. Our approach differs from previous efforts in this domain in that it first reconstructs accurately the 3D environment from a...
This paper proposes a novel algorithm which simultaneously inpaints structures and textures of damaged images. In past years, people copy the pixels, which come from the surrounding neighborhood or selected example, into damaged region along isophate direction. This might cause such result as blur edges, which looks "unreasonable" to human eyes. This algorithm decomposes the image into two...
This paper proposes a novel algorithm which simultaneously inpaints structures and textures of damaged images. In past years, people copy the pixels, which come from the surrounding neighborhood or selected examplar, into damaged region along isolation direction. This might cause such result as blur edges, which looks "unreasonable" to human eyes. We perform segmentation based on PCNN which...
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