Seed Point Selection Method for Triangle Constrained Image Matching Propagation

Zhu, Qing; Wu, Bo; Xu, Zhixiang

doi:10.1109/lgrs.2005.861735

Cited by 54 publications

(32 citation statements)

References 4 publications

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“…In order to select the n_cell i corner points among the N i available corner points in each cell, the multiplication of the Harris measure by the information entropy of corners is used as the ranking criteria. Information entropy, which has a strong relationship with the correct matching probability (Zhu et al, 2006), is calculated in the surrounding circular region of each corner point with a radius of r = 7 pixels. In cases where it is not possible to select the required n_cell i corners in a grid cell, the lack of corners is compensated by a proportional increase in the number of features assigned to other cells.…”

Section: Methodology Of the Proposed Approachmentioning

confidence: 99%

Image Matching of Satellite Data Based on Quadrilateral Control Networks

Sedaghat

Ebadi

Mokhtarzade

2012

The Photogrammetric Record

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Automatic image matching of satellite data is a difficult process due to the complex characteristics of such image pairs, including significant translation, rotation, scaling and illumination differences. A new method is proposed where, initially, a pre‐registration is performed to coarsely align the input and reference images. Next, a dense set of corner points are extracted using the Harris operator. The strongest conjugate corner points are determined and the accuracy is improved by using least squares matching to construct a precise braced quadrilateral control network in the two images. Once the consistency of the established network pairs has been determined, it is used as a framework to match the remaining corner points. Comprehensive evaluations of the proposed method on a variety of image pairs from different sensors prove its efficiency with sub‐pixel positional accuracy.

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Section: Methodology Of the Proposed Approachmentioning

confidence: 99%

Image Matching of Satellite Data Based on Quadrilateral Control Networks

Sedaghat

Ebadi

Mokhtarzade

2012

The Photogrammetric Record

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“…However, it can be performed before pairwise matching begins in practical applications such as the landmark-based navigation [23,24]. In these applications, a detailed understanding of the environments is usually required for selecting a small number of features.…”

Section: Computational Complexitymentioning

confidence: 99%

SIFT Saliency Analysis for Matching Repetitive Structures

Yang

et al. 2017

Mathematical Problems in Engineering

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The ambiguity resulting from repetitive structures in a scene presents a major challenge for image matching. This paper proposes a matching method based on SIFT feature saliency analysis to achieve robust feature matching between images with repetitive structures. The feature saliency within the reference image is estimated by analyzing feature stability and dissimilarity via MonteCarlo simulation. In the proposed method, feature matching is performed only within the region of interest to reduce the ambiguity caused by repetitive structures. The experimental results demonstrate the efficiency and robustness of the proposed method, especially in the presence of respective structures.

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“…Zhu [22] indicated that the probability of correct matching and information content enjoy strong correlation. This means that the probability of correct matching increases with increasing information entropy.…”

Section: Piecewise Correction With Optimized Cps Based On Distribumentioning

confidence: 99%

An Effective Correction Method for Seriously Oblique Remote Sensing Images Based on Multi-View Simulation and a Piecewise Model

Wang

Liu

Zhao

et al. 2016

Sensors

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Conventional correction approaches are unsuitable for effectively correcting remote sensing images acquired in the seriously oblique condition which has severe distortions and resolution disparity. Considering that the extraction of control points (CPs) and the parameter estimation of the correction model play important roles in correction accuracy, this paper introduces an effective correction method for large angle (LA) images. Firstly, a new CP extraction algorithm is proposed based on multi-view simulation (MVS) to ensure the effective matching of CP pairs between the reference image and the LA image. Then, a new piecewise correction algorithm is advanced with the optimized CPs, where a concept of distribution measurement (DM) is introduced to quantify the CPs distribution. The whole image is partitioned into contiguous subparts which are corrected by different correction formulae to guarantee the accuracy of each subpart. The extensive experimental results demonstrate that the proposed method significantly outperforms conventional approaches.

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Seed Point Selection Method for Triangle Constrained Image Matching Propagation

Cited by 54 publications

References 4 publications

Image Matching of Satellite Data Based on Quadrilateral Control Networks

Image Matching of Satellite Data Based on Quadrilateral Control Networks

SIFT Saliency Analysis for Matching Repetitive Structures

An Effective Correction Method for Seriously Oblique Remote Sensing Images Based on Multi-View Simulation and a Piecewise Model

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