视差约束的改进Hough变换多光谱影像匹配方法

doi:10.3969/j.issn.1001-2400.2015.06.017

Abstract

Abstract:

To overcome the problems of image matching caused by different charactors and the grey-level in every spectrum of the airborne filter multispectral imager for the same target， a matching method for multispectral images based on improved Hough transformation with disparity constraint is presented. Firstly, we get the N layer pyramid images of the two multispectral images for registration by down-sampling, and then calculate the transformation parameters of each layer between the left and right images progressively. In this progress, the transformation parameters of the two adjacent top Pyramid images can be calculated by using the feature points extracted by the SIFT operator, and the transformation parameters of the other adjacent Pyramid images can be calculated by using the transformation parameters of their upper images and the improved Hough transformation. At the same time, the attitude parameters and the geometric transform relation calculated from the upper layer between the images can be used to improve the matching speed and reliability. By processing two airborne flight multispectral images with 1415×1415 pixels, this approach only takes 78 secends, and its registration accuracy can reach 065 pixels.

Key words: pyramid method, multispectral, improved Hough transformation, progressive image matching

CLC Number:

TP751

ZHAO Baowei;XIANGLI Bin;HUANG Min;LV Qunbo;ZHANG Guifeng. Matching method for multispectral images based on improved hough transformation with disparity constraint[J].J4, 2015, 42(6): 94-98.

References

［1］徐晓轩, 林海波, 俞钢, 等. 小型线形可变滤光片分光的可见成像光谱仪及其特性研究［J］. 光谱学与光谱分析, 2002, 22(5): 714.
Xu Xiaoxuan, Lin Haibo, Yu Gang, et al. Reseatch of Image Spectrometer Using Linear Variable Interference Filter［J］. Spectroscopy and Spectral Analysis, 2002, 22(5): 714.
［2］ Darren T, Arko L, Zbyněk M, et al. Spatial Co-registration of Ultra-high Resolution Visible, Multispectral and Thermal Images Acquired with a Micro-UAV over Antarctic Moss Beds［J］. Remote Sensing, 2014, 6(5): 4003-4024.
［3］ Lee I H, Choi T S. Accurate Registration Using Adaptive Block Processing for Multispectral Images［J］. IEEE Transactions on Circuits And Systems for Video Technology, 2013, 23(9): 1491-1501.
［4］ Zitov B, Flusser J. Image Registration Methods: a Survey［J］. Image and Vision Computing, 2003, 21(11): 977-1000.
［5］ Wang F, Vemuri B C, Rao M. Cumulative Residual Entropy, a New Measure of Information ＆ Its Application to Image Alignment［J］. Computer Vision, 2003, 86(1): 112-114.
［6］钟灿. 非常规航摄影像定位方法及精度评定［D］. 武汉: 武汉大学, 2013.
［7］ Lowe D G. Distinctive Image Features from Scale-invariant Interest Points［J］. International Journal of Computer Vision, 2004, 60(2): 91-110.
［8］ Sajid S, Robert S. A Robust SIFT Descriptor for Multispectral Images［J］. IEEE Signal Processing Letters, 2014, 21(4): 400-403.
［9］ Li A L, Zhang B H. Registration Algorithm of Panchromatic and Multi-spectral Images Based on SIFT and RANSAC［C］//Symposium on Photonics and Optoelectronics. Piscataway: IEEE, 2012: 1-4.
［10］罗文超, 刘国栋, 杨海燕. SIFT和改进的RANSAC算法在图像配准中的应用［J］. 计算机工程与应用, 2013, 49 (15): 147-149.
Luo Wenchao, Liu Guodong, Yang Haiyan. Application of SIFT and Advanced RANSAC Algorithm on Image Registration［J］. Computer Engineering and Applications, 2013, 49(15): 147-149.
［11］ Goncalves H, Corte-Real L, Goncalves J A. Automatic Image Registration through Image Segmentation and SIFT［J］. IEEE Transactions on Geoscience and Remote Sensing, 2011, 49(7): 2589-2600.
［12］ Schneider M, Suri S, Reinartz P, et al. Matching of High-resolution Optical Data to a Shaded DEM［C］//International Geoscience and Remote Sensing Symposium. Piscataway: IEEE, 2009: 37-40.

[1]	LIU Shuai;MA Wenping;YANG Shuyuan;CHEN Puhua. Multispectral imagery denoising using hierarchical dictionary learning with spatial-spectral information [J]. Journal of Xidian University, 2017, 44(4): 174-180.
[2]	LIANG Wei;ZENG Ping;ZHENG Haihong;LUO Xuemei. Multispectral image compression algorithm based on composite transform [J]. J4, 2015, 42(4): 33-40.
[3]	LIU Xin;ZHANG Jianqi;WANG Xiaorui;LIU Dongdong;ZHANG Fudi. Method for predicting the operating range of multispectral thermal imaging systems [J]. J4, 2013, 40(2): 153-158.
[4]	WANG Ke-yan1;WU Cheng-ke1;DENG Jia-xian2;KONG Fan-qiang1;GUO Jie1. Compression of interferential multispectral images based on empirical data decomposition [J]. J4, 2007, 34(6): 900-905.
[5]	XIAO Jiang1;WU Cheng-ke1;LI Yun-song1;XIANG Li-bin2;YANG Jian-feng2. Compression of the multispectral image by the three-dimensional EBCOT coding algorithm [J]. J4, 2005, 32(4): 549-554.

Matching method for multispectral images based on improved hough transformation with disparity constraint

PDF (PC)

Like

Knowledge

Cited

Abstract

Cite this article

share this article

References

Related Articles 5

Metrics

Comments

Recommended 10