基于聚類的非共線多CCD遙感圖像誤匹配點去除方法

黃利; 尤紅建

doi:10.11999/JEIT170043

基于聚類的非共線多CCD遙感圖像誤匹配點去除方法

doi: 10.11999/JEIT170043

黃利¹,
尤紅建¹

基金項目:

國家自然科學(xué)基金(41001214)

計量
- 文章訪問數(shù): 1142
- HTML全文瀏覽量: 149
- PDF下載量: 198
- 被引次數(shù): 0
出版歷程
- 收稿日期: 2017-01-12
- 修回日期: 2017-05-11
- 刊出日期: 2017-10-19

A Method of Mismatching Points Elimination of Non-collinear Multiple CCDs Remote Sensing Images Based on Clustering Algorithm

HUANG Li¹,
YOU Hongjian¹

Funds:

The National Nature Science Foundation of China (41001214)

摘要

摘要: 針對非共線多CCD遙感圖像匹配點的分布特點，該文提出一種基于聚類的誤匹配點去除方法。首先，根據(jù)匹配點的沿軌方向偏移量曲線，獲取匹配點的多維特征向量。然后，對匹配點集進行聚類處理，將所有點聚為一個類簇，最后根據(jù)簇半徑序列曲線的變化趨勢區(qū)分正確點和誤匹配點。通過天繪1號02星全色遙感圖像的實驗和處理，結(jié)果表明在誤匹配點去除和正確匹配點保留方面所提算法與其它方法相比具有更好性能。
- 遙感圖像 /
- 非共線 /
- 電荷耦合器件 /
- 誤匹配點 /
- 聚類
Abstract: Considering the distribution characteristic of the matching points of non-collinear multiple Charge- Coupled Device (CCD) remote sensing images, a new method based on clustering to eliminate the mismatching points is proposed. First, the multi-dimensionality feature vector of matching points is obtained on the basis of the disparity curve in along-track direction. Second, all points are clustered to one cluster. Finally, the points are marked off according to the variation trend of the semi-diameter of the cluster. The experiment results running on the panchromatic image of mapping satellite 1-02 show that the method has better performance on eliminating the mismatched points and keeping the matched points.
- Remote sensing images /
- Non-collinear /
- Charge-Coupled Device (CCD) /
- Mismatching points /
- Clustering

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參考文獻(24)

TANG Xinming, HU Fen, WANG Mi, et al. Inner FoV stitching of spaceborne TDI CCD images based on sensor geometry and projection plane in object space[J]. Remote Sensing, 2014, 6(7): 6386-6406. doi: 10.3390/rs6076386.

SUN Tao, LONG Hui, and LIU Baocheng. Application of attitude jitter detection based on short-time asynchronous images and compensation methods for Chinese mapping satellite-1[J]. Optics Express, 2015, 23(2): 1395-1410. doi: 10.1364/OE.23.001395.

潘俊, 胡芬, 王密, 等. 一種非共線TDI CCD成像數(shù)據(jù)內(nèi)視場拼接方法[J]. 測繪學(xué)報, 2014, 43(11): 1165-1173. doi: 10. 13485/jcnki.11-2089.2014.0180.

PAN Jun, HU Fen, WANG Mi, et al. An inner FOV stistching method for non-collinear TDI CCD inages[J]. Acta Geodaetica et Cartographica Sinica, 2014, 43(11): 1165-1173. doi: 10.13485/jcnki.11-2089.2014.0180.

李世威, 劉團結(jié), 王宏琦. 基于圖像匹配的CBERS-02B衛(wèi)星HR相機圖像拼接方法[J]. 遙感技術(shù)與應(yīng)用, 2009, 24(3): 374-378.

LI Shiwei, LIU Tuanjie, and WANG Hongqi. Image mosaic for TDICCD pushbroom camera image based on image matching[J]. Remote Sensing Technology and Application, 2009, 24(3): 374-378.

ZITOVA B and FLUSSER J. Image registration methods: A survey[J]. Image and Vision Computing, 2003, 21(11): 977-1000. doi: 10.1016/S0262-8856(03)00137-9.

FISCHLER M A and BOLLES R C. Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography[J]. Communication ACM, 1981, 24(6): 381-395. doi: 10.1145/ 358669.358692.

LI Bin, MING Delie, YAN Wenwen, et al. Image matching based on two-column histogram hashing and improved RANSAC[J]. IEEE Geoscience and Remote Sensing Letters, 2012, 11(8): 783-787. doi: 10.1109/LGRS.2013.2295115.

馬旭燕, 袁媛, 汪承義, 等. 高分辨率遙感圖形配準(zhǔn)控制點均勻化算法[J]. 遙感信息, 2016, 31(3): 24-30. doi: 10.3969/ j.issn.1000-3177.2016.03.004.

MA Xuyan, YUAN yuan, WANG Chengyi, et al. A control point uniformization algorithm for high-resolution remote sensing image registration[J]. Remote Sensing Information, 2016, 31(3): 24-30. doi: 10.3969/j.issn.1000-3177.2016.03.004.

吳君涵, 余柏蒗, 彭晨, 等. 基于移動激光掃描點云數(shù)據(jù)和遙感圖像的建筑物三維模型快速建模方法[J]. 測繪與空間地理信息, 2016, 39(1): 25-34.

WU Junhan, YU Bailang, PENG Chen, et al. A metnod for fast modeling of 3D building from mobile laser scanning point clouds and remote sensing data[J]. Geomatics Spatial Information Technology, 2016, 39(1): 25-34.

ZAHRA H and MEHDI N. Image registration based on SIFT features and adaptive RANSAC transform[C]. International Conference on Communication and Signal Processing, India, 2016: 1087-1091.

龍小祥, 王小燕, 鐘惠敏. 星載焦面視場拼接TDI CCD相機成像質(zhì)量及處理方法分析[J]. 中國科學(xué): 信息科學(xué), 2011, 41(增刊): 19-31.

LONG Xiaoxiang, WANG Xiaoyan, and ZHONG Huimin. Analysis of image quality and processing method of space- borne focal plane view splicing TDI CCD camera[J]. Science of China: Information of Science, 2011, 41(Suppl.): 19-31.

胡芬. 三片非共線TDI CCD成像數(shù)據(jù)內(nèi)視場拼接理論與算法研究[D]. [博士論文], 武漢大學(xué), 2010: 63.

HU F. Research on inner FOV stitching theories and algorithms for sub-images of three non-collinear TDI CCD chips[D]. [Ph.D. dissertation], Wuhan University, 2010: 63.

祿金波, 何斌. TDICCD相機大視場多通道遙感圖像自動拼接方法[J]. 空間科學(xué)學(xué)報, 2012, 32(1): 154-160.

LU Jinbo and HE Bin. Automatic mosaic method of large field view and multi-channel remote sensing images of TDICCD cameras[J]. Chinese Journal of Space Science, 2012, 32(l): 154-160.

JAIN A K. Data clustering: 50 years beyond k-means[C]. 19th International Conference on Pattern Recognition, Tampa, USA, 2010: 651-666. doi: 10.1016/j.patrec.2009.09. 011.

張順龍, 庫濤, 周浩. 針對多聚類中心大數(shù)據(jù)集的加速K-means聚類算法[J]. 計算機應(yīng)用研究, 2016, 33(2): 413-416. doi: 10.3969/j.issn.1001-3695.2016.02.021.

ZHANG Shunlong, KU Tao, and ZHOU Hao. Accelerate K-means for multi-center clustering of big datasets[J]. Application Research of Computers, 2016, 33(2): 413-416. doi: 10.3969/j.issn.1001-3695.2016.02.021.

SINHA A and JANA P K. A novel K-Means based clustering algorithm for big data[C]. International Conference on Advances in Computing, Communications and Informatics (ICACCI), Jaipur, India, 2016: 1875-1879. doi: 10.1109/ ICACCI.2016.7732323.

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