A Robust Image Registration Algorithm Based on Feature Points Matching

Guixi, 刘贵喜 Liu; Dongmei, 刘冬梅 Liu; Fengpeng, 刘凤鹏 Liu; Yaping, 周亚平 Zhou

doi:10.3788/aos20082803.0454

Cited by 9 publications

(5 citation statements)

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“…We can judge a point whether is an angular point [5] by calculating the eigenvalues of N, first order curvature of autocorrelation function. N is defined below.…”

Section: A Image Registrationmentioning

confidence: 99%

Research on target recognition based on edge features

Wang

Qian

Chen

2012

2012 5th International Congress on Image and Signal Processing

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A method of target recognition based on edge features of the images acquired before and after the damage is proposed to improve the accuracy of registration and recognition in Battlefield Damage Assessment. The image registration combined circle area method and angular point extraction is conducted after the preprocessing. The vector groups of edge features can be obtained from the extraction of color and textural features of the targets. By comparing the vector groups of the images, the object in the post-damage image can be recognized whether it is the target or not. The verification results indicate that the targets in minor damage can be recognized accurately and quickly.

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“…We can judge a point whether is an angular point [5] by calculating the eigenvalues of N, first order curvature of autocorrelation function. N is defined below.…”

Section: A Image Registrationmentioning

confidence: 99%

Research on target recognition based on edge features

Wang

Qian

Chen

2012

2012 5th International Congress on Image and Signal Processing

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“…For the high frequency coefficients, the fusion rules is based on local variance combining with matching threshold [6] .…”

Section: The Fusion Rulesmentioning

confidence: 99%

An Image Fusion Algorithm Based on Redundant Wavelet Transform

Shen¹,

Yang

et al. 2014

AMM

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Because of the limit of the optical lens’s depth, the objects of different distance usually cannot be at the same focus in the same picture, but multi-focus image fusion can obtain fusion image with all goals clear, improving the utilization rate of the image information ,which is helpful to further computer processing. According to the imaging characteristics of multi-focus image, a multi-focus image fusion algorithm based on redundant wavelet transform is proposed in this paper. For different frequency domain of redundant wavelet decomposition, the selection principle of high-frequency coefficients and low-frequency coefficients is respectively discussed .The fusion rule is that,the selection of low frequency coefficient is based on the local area energy, and the high frequency coefficient is based on local variance combining with matching threshold. As can be seen from the simulation results, the method given in the paper is a good way to retain more useful information from the source image , getting a fusion image with all goals clear.

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“…Feature matching method, through the image feature information extraction, can greatly reduce the matching process computation, simultaneously have better ability to adapt image rotation, scaling, gray-scale transformation, noise interference and viewpoint changes. Commonly used features, such as the edge [5][6], contour [7][8], statistical characteristics [9][10] and feature points [11][12][13][14][15], etc.…”

Section: Introductionmentioning

confidence: 99%

Infrared Image Mosaic Based on Pulse Coupled Neural Network

Zhang

Wang

et al. 2012

AMM

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According to the infrared image noise interference serious and low signal to noise ratio characteristics, an image mosaic algorithm based on pulse coupled neural network is presented in this paper. The algorithm uses the PCNN imitation of biological vision to extract edge information, adopts the Hausdorff distance as the registration similarity measure, afterwards, computes the optimal registration parameters, simultaneously, uses the weighted average fusion method to achieve image mosaic. The experimental results show that the algorithm can achieve precise image mosaic and have better robustness to noise.

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A Robust Image Registration Algorithm Based on Feature Points Matching

Cited by 9 publications

References 0 publications

Research on target recognition based on edge features

Research on target recognition based on edge features

An Image Fusion Algorithm Based on Redundant Wavelet Transform

Infrared Image Mosaic Based on Pulse Coupled Neural Network

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