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Image registration is an essential step in many image processing applications that involve multiple images for comparison, integration or analysis such as image fusion, image mosaics, image or scene change detection, and medical imaging. Image registration methods can be categorized into two major groups: the feature-based approach and the area-based approach. In area-based approach LPT was introduced...
This paper proposes an efficient and robust algorithm to recover a panorama from poorly-obtained UAV video frames contaminated with significant noise. In this algorithm, the eigen-space based neighborhood region will be introduced with our novel feature-based random M least-squares (RMLS) registration technique. Meanwhile, the corresponding similarity regions will be assigned weights according to...
Unmanned aerial vehicles (UAVs) are regularly outfitted with payloads that include high resolution surveillance cameras. These surveillance systems have provided the military with the opportunity to monitor battlefields and remote terrain, carryout reconnaissance missions and track targets all from distant ground stations without endangering UAV operators. As with any remote sensing technology there...
Automatic registration in microscopic image sequence is a classical problem, which has not been solved well so far. According to the features of medical microscopic image sequence, the SIFT feature detection method of microscopic image registration is introduced. As large dimension of the traditional SIFT descriptor and its complex algorithm, an improved algorithm of the SIFT is presented, which can...
Image registration is an essential task in many image processing applications. Log-polar transform (LPT) is a well known tool for image processing for its rotation and scale invariant properties. However it suffers from nonuniform sampling which makes it not suitable for the environment when registered images are altered or occluded. Inspired by LPT, this paper presents a new algorithm that addresses...
This paper presents a novel and efficient surface matching and visualization framework through the geodesic distance-weighted shape vector image diffusion. Based on conformal geometry, our approach can uniquely map a 3D surface to a canonical rectangular domain and encode the shape characteristics (e.g., mean curvatures and conformal factors) of the surface in the 2D domain to construct a geodesic...
In this paper, a new feature points extraction method based on the nonsubsampled contourlet transform (NSCT) is proposed for image registration. The primary motivation of this work is to determine the effectiveness of the NSCT transform for feature points extraction for the use of image registration. The performance of the proposed NSCT-based registration algorithm is demonstrated and validated in...
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