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Mapping without the sun

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fullscreen: Mapping without the sun

Monograph

Persistent identifier:: 856578517

Author:: Zhang, Jixian

Title:: Mapping without the sun

Sub title:: techniques and applications of optical and SAR imagery fusion ; Chengdu, China, 25 - 27 September 2007

Scope:: 1 Online-Ressource (III, 352 Seiten)

Year of publication:: 2007

Place of publication:: Lemmer

Publisher of the original:: GITC

Identifier (digital):: 856578517

Illustration:: Illustrationen, Diagramme, Karten

Language:: English

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2016

Document type:: Monograph

Collection:: Earth sciences

Chapter

Title:: MATRIX DECOMPOSITION AND MATRIX SOLVERS IN PHOTOGRAMMETRY. Cheng Chunquan, Deng Kazhong, Zhang Jixian, YanQin

Document type:: Monograph

Structure type:: Chapter

Contents

Table of contents

Mapping without the sun
Cover
ColorChart
Title page
Table of Content
Foreword
Scientific Committee:
Organizing Committee:
DECISION FUSION OF MULTITEMPORAL SAR AND MULTISPECTRAL IMAGERY FOR IMPROVED LAND COVER CLASSIFICATION B. Waske a, J. A. Benediktsson b’*
SYNERGISTIC USE OF OPTICAL AND INSAR DATA FOR URBAN IMPERVIOUS SURFACE MAPPING: A CASE STUDY IN HONG KONG. Liming Jiang, Hui Lin, Mingsheng Liao, Limin Yang
A NOVEL FUSION METHOD OF SAR AND OPTICAL IMAGES FOR URBAN OBJECT EXTRACTION. Jia Yonghong, Rick S. Blum,Ma Yunxia
REAL-TIME SAR SIMULATION FOR CHANGE DETECTION APPLICATIONS BASED ON DATA FUSION. Timo Balz
THE OPTIMIZING METHOD OF FUSING SAR WITH OPTICAL IMAGES FOR INFORMATION EXTRACTION. Feng Xie, Yingying Chen, Yi Lin
ORTHORECTIFYING SPACEBORNE SAR BY DEM BASED ON FINE REGISTRATION. Hongjian You, Fu Kun
DETECTION AND ANALYSIS OF EARTHQUAKE-INDUCED URBAN DISASTER BASED ON INSAR COHERENCE. M. He, X. F. He
MULTI-SCALE SAR LAND USE/LAND COVER CLASSIFICATION BASED ON CO-OCCURRENCE PROBABILITIES. Yu ZENG, Jixian ZHANG, J. L.VAN GENDEREN, Haitao LI
TERRASAR-X AND TANDEM-X: REVOLUTION IN SPACEBORNE RADAR. Ralf Duering
A MULTI-WAVELENGTH IMAGING SYSTEM FOR DETECTION OF FOREIGN FIBERS IN COTTON. Lu Dehao
A FUSION ALGORITHM OF HIGH SPATIAL AND SPECTRAL RESOLUTION IMAGES BASED ON ICA. GuoKun Zhang, LeiGuang Wang, Hongyan Zhang
A SUPER RESOLUTION RECONSTRUCTION ALGORITHM TO MULTI-TEMPORAL REMOTE SENSING IMAGES. Pingxiang Li, Jixian Zhang, Huanfeng Shen, Liangpei Zhang
COMPARISON OF MORPHOLOGICAL PYRAMID AND LAPLACIAN PYRAMID TECHNIQUES FOR FUSING DIFFERENT FOCUSING IMAGES. Jia Yonghong, Fu Xiujun, Yu Hongwei
MONITORING AND CHARACTERIZING NATURAL HAZARDS WITH SATELLITE INSAR IMAGERY. Z. Lu
PREDICTION AND SIMULATIONS OF MALAYSIAN FOREST FIRES BY MEANS OF RANDOM SPREAD. Jean Serra, Mohd Dini Hairi Suliman, and Mastura Mahmud
TEXTURE CLASSIFICATION RESEARCH BASED ON LIFTING-BASED DWT 9/7 WAVELET. Hong Zhang, Ning Shu
REMOTE SENSING IMAGE SEGMENTATION BASED SELF-ORGANIZING MAP AT MULTI-SCALE. Zhao Xi-an, Zhang Xue-wen Wei Shi-yan
A JOINT SPATIAL-TEMPORAL CLASSIFICATION AND FEATURE BOUNDARY UPDATING MODEL. P. Caccetta
THE APPLICATION RESEARCH IN ASSISTANT CLASSIFICATION OF REMOTE SENSING IMAGE BY TEXTURE FEATURES COMBINED WITH SPECTRA FEATURES. Y. M. Fang, X. Q. Zuo, Y. J. Yang, J. H. Feng
A KIND OF THE METHODS FOR SAR AND OPTICAL IMAGES FUSION BASED ON THE LIFTING WAVELET. Shao Yongshe, Chen Ying, Li Jing
SOIL MOISTURE RETRIEVAL COMBINING OPTICAL AND RADAR DATA DURING SMEX02. Chen Quan, Li Zhen, Tian Bangsen
A TARGET DETECTION METHOD BASED ON SAR AND OPTICAL IMAGE DATA FUSION. Sun Mu-han, Zhou Yin-qing, Xu Hua-ping
FUSION SAR AND OPTICAL IMAGES TO DETECT OBJECT-SPECIFIC CHANGES. Mu H. Wang, Hai T. Li, Ji. X Zhang ,Jing H. Yang
APPLICATION OF DINSAR AND GIS FOR UNDERGROUND MINE SUBSIDENCE MONITORING. YAN Ming-xing, MIAO Fang, WANG Bao-cun, QI Xiao-ying
THE DETECTION OF SUBSIDENCE AT PERMANENT FROZEN AREA IN QINGHAI-TIBETAN PLATEAU. Z. Li, C. Xie, Q. Chen
RESEARCH ON SURFACE SUBSIDENCE MONITORING WITH INSAR/GPS DATA FUSION IN MINING AREA. ZHANG Ji-chao, SONG Wei-dong, ZHANG Ji-xian, SHI Jin-feng
SEVEN YEARS OF MINING SUBSIDENCE DETECTED BY D-InSAR TECHNIQUE IN FUSHUN CITY, CHINA. Y. L. Chen, X. L. Ding, C. Huang, Z. W. Li
A METHOD ON HIGH-PRECISION RECTIFICATION AND REGISTRATION OF MULTI-SOURCE REMOTE SENSING IMAGERY. Bin Liu, Guo Zhang, Xiaoyong Zhu, Jianya Gong
STUDY ON TIE POINT SELECTION FOR CO-REGISTRATION OF DIFFERENT RESOLUTION IMAGERY. Zhen Xiong, Yun Zhang
THE STUDY OF SPACE INTERSECTION MODEL BASED ON DIFFERENT-SOURCE HIGH RESOLUTION RS IMAGERY. Weixi Wang, Qing Zhu
AN OPTIMIZATION HIGH-PRECISION REGISTRATION METHOD OF MULTI-SOURCE REMOTE SENSING IMAGES. LIN Yi, JIAN Jianfeng , ZHANG Shaoming, XIE Feng
A METHODOLOGY OF LUCC CHANGE DETECTION BASED ON LAND USE SEGMENT. Ning Shu, Hong Zhang, Xue Li, Yan Wang
APPLICATION OF MULTI-TEMPORAL TM (ETM+) IMAGE IN MONITORING MINING ACTIVITIES AND RELATED ENVIRONMENT CHANGES: A CASE STUDY AT DAYE, HUBEI, CHINA. Shiyong YU, Zhihua CHEN, Yanxin WANG
LAND COVER CHANGE AND CLIMATIC VICISSITUDE RESEARCH IN HEADSTREAM REGIONOF YELLOW RIVER IN THE NINETIES OF THE TWENTIETH CENTURY. DAI Ji-guang, YANG Tai-bao, REN Jia-qiang
LAND USE CHANGES IN THREE GORGES RESERVOIR AREA IN RECENT 30 YEARS. Sun xiaoxia, Zhang jixian, Liu zhengjun
AUTOMATED VEHICLE INFORMATION EXTRACTION FROM ONE PASS OF QUICKBIRD IMAGERY. Zhen Xiong, Yun Zhang
CLASSIFICATION OF LAND TYPES IN MINERAL AREAS BASED ON CART. Wenbo Wu, Yuping Chen, Jiaojiao Meng, Tingjun Kang
OBJECT-ORIENTED CLASSIFICATION OF HIGH-RESOLUTION REMOTE SENSING IMAGERY BASED ON MRF AND SVM. GU Haiyan, LI Haitao, ZHANG feng, HAN Yanshun, YANG Jinghui
EXTENSIBLE LAND USE AND LAND COVER CLASSIFICATION FRAMEWORK DESIGN BASED ON REMOTELY SENSED DATA. Wang Juanle
THE ROAD EXTRACTION IN THE AREA COVERED WITH HIGH VEGETATION USING THE FUSION IMAGE OF SAR AND TM. Shen Jin-li, Yu Wu-yi, Qi Xiao-ping, Zhang Yi-min
DISCRETE WAVELET-BASED FUSION OF TM MULTI-SPECTRAL IMAGE AND SAR IMAGE DATA. Liang Shouzhen, Li Lanyong
FUSING SAR AND OPTICAL IMAGES BASED ON COMPLEX WAVELET TRANSFORM. Shuai Xing, Qing Xu
A COMPREHENSIVE QUALITY EVALUATION METHOD OF INFORMATION FUSION FROM HIGH-RESOLUTION AIRBORNE SAR AND SPOT5 IMAGES. Wenqing Dong, Qin Yan,
A SIMPLIFIED FUSION METHOD BASED ON SYNTHETIC VARIABLE RATIO. Pang Xinhua, Xi Bin, Chen Luyao, Pan Yaozhong,, Zhuang Wei
A NOVEL IMAGE FUSION METHOD BASED ON 2DPCA IN REMOTE SENSING. Xue-ming Wu, Wu-nian Yang
A METHOD TO DETERMINE SPATIAL RESOLUTION OF REMOTE SENSING FUSED IMAGE QUANTITATIVELY. X. J. Yue, L. Yan, G. M. Huang
A NEW PAN-SHARPENING ALGORITHM AND ITS APPLICATION IN GEOGRAPHIC FEATURES INFORMATION EXTRACTION. ZHU Lijiang
RESEARCH ON THE PROCESS OF LAND USE/COVER CHANGE IN THREE GORGES RESERVOIR AREA IN RECENT 30 YEARS. SHAO Huai-Yong, XIAN Wei, LIU Xue-Mei, YANG Wu-Nian
THE STUDY OF LAND USE CHANGE DETECTION BASED ON SOLE PERIOD RS IMAGE. Song Weidong, Wang Jingxue, Qin Yong
ANALYSIS OF THE LAND USE OF SHENYANG MINING DISTRICT AND ITS DRIVING FORCE. Kaixuan Zhang, Wenbo Wu, Chongchang Wang, Tingjun Kang
REMOTE-SENSING IMAGE COMPRESSION BASED ON FRACTAL THEORY. Chao Mu, Qin Yan, Jie Yu, Huiling Qin
MATRIX DECOMPOSITION AND MATRIX SOLVERS IN PHOTOGRAMMETRY. Cheng Chunquan, Deng Kazhong, Zhang Jixian, YanQin
INVESTIGATING SEVERAL POINT CLOUD REGISTRATION MOTHEDS. Luo Dean, Zhou Keqin, Huang Jizhong
THE ACCURACY ASSESSMENT OF ORTHORECTIFIED ASTER IMAGE. Li Baipeng, Yan Qin, Chen Chunquan
EPIPOLAR RESAMPLING OF DIFFERENT TYPES OF SATELLITE IMAGERY. Jiaying Liu, Guo Zhang, Deren Li
REFINEMENT AND EVALUATION OF BEIJING-1 ORTHORECTIFICATION BASED ON RFM. Jianming Gong, Xiaomei Yang, Chenghu Zhou, Xiaoyu Sun, Cunjin Xue
LAND COVER CLASSIFICATION BY IMPROVED FUZZY C-MEAN CLASSIFIER. ZHAO Quan-hua, SONG Wei-dong, Bao Yong
RESEARCH ON GRIDDING PROCESSING STRATEGIES OF REMOTE SENSING IMAGE SEGMENTATION BY REGION GROWTH. ZHU Hong-chun, ZHANG Ji-xian, LI Hai-tao, YANG Jing-hui, LIU Hai-ying
TEXTURE ANALYSIS IN INFORMATION EXTRACT IN THE HIGH RESOLUTION RS IMAGES LU Shuqiang
THE STUDY OF REMOTE SENSING IMAGE INFORMATION EXTRACTION TECHNIQUES BASED ON KNOWLEDGE. Wenbo Wu, Jiaojiao Meng, Yuping Chen, Jing Chen
A NEW METHOD OF SIMULATION OF INTERFEROGRAM IMAGE FOR REPEAT-PASS SAR SYSTEM. Jianmin Zhou, Zhen Li, Xinwu Li, Chou Xie
COMPARISON AND IMPROVEMENT OF POSITION METHODS OF AIRBORNE STEREO SAR IMAGES. H. D. Fan, K. Z. Deng, G. M.Huang, Z. Zhao., X. J. Yue, X. M. Luo, Y. F. Ling
STUDY ON TOPOGRAPHIC MAP UPDATING WITH HIGH RESOLUTION AIRBORNE SAR IMAGE. X .M. Luo, G. M. Huang, Z. Zhao
AN EXPERIMENT OF HIGH RESOLUTION SAR IMAGE IN DYNAMIC MONITORING THE CHANGE OF CONSTRUCTION LAND. CaoYinxuan, Zhang Yonghong, YanQin, ZhaoZheng
RESEARCH ON STATISTICS AND SPATIAL ANALYSIS OF DRAINAGE BASIN'S IMPORTANT GEOGRAPHICAL ELEMENTS. Liu Ping, Liu Jiping, Zhao Rong
THE RESEARCH AND ESTABLISHMENT OF IMAGE DATABASE SYSTEM BASED ON ORACLE. Li Lanyong, Song Weidong, Chen Zhaoliang, Zhao Hongfeng
SITE SELECTION FOR SATELLITE GEOMETRIC TEST RANGE IN CHINA. Xinxin Zhu, Guo Zhang, Qing Zhu, Xinming Tang
ANALYSIS OF IMAGES GEOMETRIC RECTIFICATION FOR QUICKBIRD. WANG Chong-chang , WANG Li-li, Zhang Li, Zhang Kai-xuan, Ma Zhen-li, ZHANG Zhen-yong
RESEARCH ON DYNAMIC SYMBOL BASE. Yang ping, Tang Xinming, Wang Shengxiao, Lei Bing, Wang Huibing
DETERMINATION OF CHLOROPHYLL CONCENTRATION IN THREE GORGES DAM USING CHRIS/PROBA IMAGE DATA. GAI Li-ya, LIU Zheng-jun,ZHANG Ji-xian
RESEARCH ON LAND SANDY DESERTIFICATION WITH REMOTE SENSING -Take Qinghai Lake Areas as an example. Jian Ji, Chen Yuanyuan, Yang wunian, Tang nengfu
METHODS AND APPLICATION OF QUALITY ASSESSMENT FOR REMOTE SENSING IMAGE COMPRESSION. ZHAI Liang, TANG Xinming, ZHANG Guo, ZHU Xiaoyong
ON-ORBIT MTF ESTIMATION METHODS FOR SATELLITE SENSORS. LI Xianbin, JIANG Xiaoguang, Tang Lingli
AUTHOR INDEX
KEYWORDS INDEX
Cover

Full text

Direct solvers for sparse matrices, including Gaussian 
Elimination, frontal, multifrontal and supemodal, involve much 
more complicated algorithms than for dense matrices. The 
main complication is due to the need for efficiently handling 
the fill-in in the factors L and U. A typical sparse solver 
consists of four distinct steps as opposed to two in the dense 
case: 
1. An ordering step that reorders the rows and columns such 
t that the factors suffer little fill, or that the matrix has 
special structure, such as block-triangular form. 
2. An analysis step or symbolic factorization that determines 
the nonzero structures of the factors and creates suitable 
data structures for the factors. 
3. Numerical factorization that computes the L and U factors. 
4. A solve step that performs forward and back substitution 
using the factors. 
4.1 Intel PARDISO 9.0 
Intel® Math Kernel Library (Intel® MKL) offers highly 
optimized, extensively threaded math routines for scientific, 
engineering, and financial applications that require maximum 
performance. 
Multiprocessors with the PARDISO Direct Sparse Solver - an 
easy-to-use, thread-safe, high-performance, and memory- 
efficient software library licensed from the University of Basel. 
Intel MKL also includes a Conjugate Gradient iterative solver 
with a flexible reverse communication interface. 
The package PARDISO is a thread-safe, high-performance, 
robust, memory efficient and easy to use software for solving 
large sparse symmetric and unsymmetric linear systems of 
equations on shared memory multiprocessors. The solver uses a 
combination of left- and right-looking Level-3 BLAS 
supemode techniques to exploit pipelining parallelism and 
memory hierarchies. In order to improve sequential and 
parallel sparse numerical factorization performance, the 
algorithms are based on a Level-3 BLAS update and pipelining 
parallelism is exploited with a combination of left- and right 
looking supemode techniques. 
For sufficiently large problem sizes numerical experiments 
demonstrate that the scalability of the parallel algorithm is 
nearly independent of the shared-memory multiprocessing 
architecture and speedup of up to seven using eight processors 
have been observed. The approach is based on OpenMP 
directives and has been successfully tested on the following 
parallel computers: COMPAQ AlphaServer, AMD Opteron, 
SGI Origin 2000, SUN Enterprise Server, Intel Pentium 
IV/Itanium(R) with RedHat LINUX, NEC SX-5, and Cray J90 
and IBM Regatta SMPs. 
4.2 UMFPACK 
UMFPACK is a set of routines for solving unsymmetric sparse 
linear systems, Ax = b, using the Unsymmetric MultiFrontal 
method and direct sparse LU factorization. It is written in 
ANSI/ISO C, with a MATLAB interface. UMFPACK relies on 
the Level-3 Basic Linear Algebra Subprograms (dense matrix 
multiply) for its performance. This code works on Windows 
and many versions of Unix (Sun Solaris, Red Hat Linux, IBM 
AIX, SGI IRIX, and Compaq Alpha). 
UMFPACK was developed by Timothy A. Davis from the 
University of Florida, Gainesville, USA. Distributed under the 
GNU LGPL license. 
The famous math software MATLAB also use UMFPACK as 
its solver. It represent today’s highest level and many other 
solvers consider it as standard to compare. 
4.3 GRUS SPARSE SOLVER 
GSS(GRUS SPARSE SOLVER) is a software for large sparse 
matrix solving. It is written in ANSI/ISO C,can be work well 
with many sort of data and most of operating system platform. 
GSS uses new models and many new algorithms at the 
symbolic-analysis phase. GSS uses multifrontal method to 
factor A to LU, it supports complete pivoting, partial 
pivoting ,rook-pivoting and static pivoting . The tests by 
comparing the time cost of computing large mounts of matrices 
show that its average capability even better than UMFPACK in 
many field such as the max matrix order number they could 
work and their computing speed, the time GSS only cost one 
third of that UMFPACK used. 
/ >jyd xoiciou x/- an itijup: itfiflwXOK'GE3 /lda 
There is no single algorithm or software that is best for all 
types of linear systems. Some software is targeted for special 
matrices such as symmetric and positive definite, some is 
targeted for the most general cases. 
5 APPLICATION IN PHOTOGRAMMETRY 
Matrix computation are widely used in Photogrammetry such 
as Complicated coordinate translation, Adjustment 
calculation ,image enhance, image transform, image analysis 
and other image processing techniques. For a image data can 
naturally form an int matrix, image process can easily be 
translated to matrix calculation. 
Based on Meschach library the following example is core 
content of a large block indirect adjustment programme in 
photogrammetry filed to solve for the unknowns vector X of 
adjustment values in the error equations: 
V=AX-L weight P 
The coefficient matrix A is a large band sparse matrix whose 
order number may excess 10,000. L is the constant vector and 
V is error vector. A,L,P are in parameters, the others are out 
parameters. 
/Ism Li to 3V)to3vjo:;b srfr , T 2o ¿aituAoo. adi qu coisrn k v k"io 
#define MAXM 10 
sp Adj ustLS( S PM AT *A, VEC *L, SPMAT *P, VEC 
*Xout,VEC *V, double &m0) 
{ 
SPMAT *AT,*Temp,*N; 
VEC *b,*u,*ll; 
int numsteps; 
b-v_get(A->n); 
u=v_get(A->m); 
AT=sp_get( A->n, A->m,M AXM); 
for(int i=0;i<A->m;i++) 
for(int j=0;j<A->n;j-H-) 
sp set_val(AT,j ,i, sp_get_val(A,i,j));//AT=A A T 
Temp=sp_get(A->n,A->m,MAXM); 
N=sp_get( A->n, A->n,M AXM); 
sp_mltadd(AT,P,1.0,Temp); 
sp_mltadd(Temp,A,l .0,N); 
sp mv mlt(Temp,L,b); 
T emp=sp_resize(T emp, A->n, A->n); 
Temp = sp_copy(N); 
spICHfactor(T emp); 
Xout = iter_spcg(N,Temp,b,le-7,Xout,1000,&num_steps); 
//Xout out 
11 = v_get(L->dim); 
sv_mlt(-l,L,ll); 
sp_mv_mlt(A,Xout,V);//V out

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