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In this paper, an improved scale-invariant feature transform (SIFT) algorithm for synthetic aperture radar (SAR) image matching is proposed. Initially, feature descriptors based on gradient ratio (GR) are constructed by utilizing traditional SIFT method. In order to measure the matching degree between images, the similarities of the descriptors are then calculated via the symmetry kullback-leibler...
Image mosaic is an important branch in the field of image processing. This paper designs and realizes an image mosaic technique based on the information of edge. The technology is suitable for engineering application. First of all, two images of the adjoining frames are processed by convolution operation, get the edge images. And then we cut edge image into pieces and compute their spatial frequency...
This paper presents a fast and reliable approach for detecting 3D line segment from 3D point clouds. The main idea is to discover weak matching of line segments by re-projecting 3D point to 2D image plane and infer 3D line segment by spatial constraints. On the basis of 2D Line Segment Detector (LSD) and multi-view stereo, the proposed algorithm firstly re-projects the spatial point clouds into planar...
When computing optical flow with region-based matching, very few of them can be reliably obtained, especially for the high-contrast areas or those with little texture. Instead of using a single pixel from the reference frame, non-deterministic motion utilizes multiple pixels within a neighborhood to represent the corresponding pixel in the current frame. Although remarkable improvement has been made...
This paper presents a novel depth recovery technique of bifocus imaging system which may produce two focus images by independent focal lengths. Depth information can be extracted from the disparity between two focus images. This paper will propose the depth recovery formula and related algorithms such as feature extraction, sub-pixel matching, and center estimation. Experiments on real scene images...
This paper presents a novel approach for depth recovery based on bifocus imaging. The imaging system with bifocus lenses may focus at different focal lengths of the same scene to produce bifocus images. Depth information can be extracted from the disparities between the image pair. This paper has given the detailed analysis of the system parameters and their appropriate values in long range detection...
Handling numerous unordered images for scene reconstruction and categorization attracts increasing interests for commercial and scientific efforts. In this paper, we address the issue of efficient organization of content-related images from plenty of input images on several scenes with contaminated ones. First a robust view-similarity measure is proposed and the images can be categorized effectively...
This paper proposes an efficient approach to find clusters of spatially related scene images collected from the website. Our method firstly builds a guide table, in which the ranked results are given according to the relevance scores of image pairs obtained by the image retrieval methods. Then the image clusters are generated by repeatedly choosing a seed image and performing query expansion directed...
This paper focuses on the multi-view feature matching problem from unordered image sets. Firstly, an efficient and effective high dimensional feature matching algorithm is proposed, so called ELSH (extended local sensitive hash), which can significantly improve matching accuracy at fast speed. Secondly, a novel unsupervised image grouping strategy is proposed to cluster the unordered images into content-related...
Image matching is a fundamental task of many problems in computer vision. This paper presents a novel local feature descriptor based on the gradient distance and orientation histogram (GDOH), which can be used for reliably matching between different views of a scene for wide baseline. The proposed descriptor is invariant to image scale, rotation, illumination and partial viewpoint changes. At present,...
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