• Proceedings of the KSRS Conference
• /
• 2004.10a
• /
• pp.208-211
• /
• 2004

Landmark matching is one of an important algorithm for navigation of satellite images. This paper proposes a fast landmark matching algorithm using a MGLI (Moving Guide-Line Image). For searching the matched point between the landmark chip and a part of image, correlation matrix is used generally, but the full-sized correlation matrix has a drawback requiring plenty of time for matching point calculation. MGLI includes thick lines for fast calculation of correlation matrix. In the MGLI, width of the thick lines should be determined by satellite position changes and navigation error range. For the fast landmark matching, the MGLI provides guided line for a landmark chip we want to match, so that the proposed method should reduce candidate areas for correlation matrix calculation. This paper will show how much time is reduced in the proposed fast landmark matching algorithm compared to general ones.

• Journal of Korean Society for Geospatial Information Science
• /
• v.5 no.2 s.10
• /
• pp.99-110
• /
• 1997

Image matching to determine the conjugate points in stereo photos is the one of the most important subject in digital photogrammetry and many researches In digital photogrammetric field are on going to automate the image matching process. In this study, we analyzes the effect of allowable correlation coefficient, which controls the accuracy in areal based image matching, on the accuracy of digital photogrammetry. So, some areal based matching methods such as image correlation coefficient matching, image Pyramid matching and interest point matching, are implemented, and the effect of allowable correlation coefficient on accuracy of digital photogrammetry in each method is analyzed. As a result of this study, a method to determine the optimal correlation coefficient is presented.

• Korean Journal of Remote Sensing
• /
• v.34 no.6_2
• /
• pp.1251-1260
• /
• 2018

High-quality sea-ice surface models generated from aerial images can be used effectively as field data for developing satellite-based remote sensing methods but also as analysis data for understanding geometric variations of Arctic sea-ice. However, the lack of texture information on sea-ice surfaces can reduce the accuracy of image matching. In this paper, we analyze the performance of matching cost functions for homogeneous sea-ice surfaces as a part of high-quality sea-ice surface model generation. The matching cost functions include sum of squared differences (SSD), normalized cross-correlation (NCC), and zero-mean normalized cross-correlation (ZNCC) in image domain and phase correlation (PC), orientation correlation (OC), and gradient correlation (GC) in frequency domain. In order to analyze the matching performance for texture changes clearly and objectively, a new evaluation methodology based on the principle of object-space matching technique was introduced. Experimental results showed that it is possible to secure reliability and accuracy of image matching only when optimal search windows are variably applied to each matching point in textureless regions such as sea-ice surfaces. Among the matching cost functions, NCC and ZNCC showed the best performance for texture changes.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
• /
• 2007.04a
• /
• pp.187-190
• /
• 2007

This study is for analyzing best band in image matching using correlation coefficient of left and right images of stereo image pair, lot red, green, blue band images separated from color aerial photo and gray image converted from the same color aerial photo image. The image matching is applied to construct Digital Elevation Model(DEM) or terrain data. The correlation coefficients and variation by change of pixel patch size are computed from pixel patches of which sizes are $11{\times}11{\sim}101{\times}101$. Consequently, the correlation coefficient in red band image is highest. The lowest is in blue band. Therefore, to construct terrain data using image matching, the red band image is preferable. As the size of pixel patch is growing, the correlation coefficient is increasing. But increasing rate declines from $51{\times}51$ image patch size and above. It is proved that the smaller pixel patch size than $51{\times}51$ is applied to construct terrain data using image matching.

• ETRI Journal
• /
• v.33 no.3
• /
• pp.401-406
• /
• 2011

This paper presents a fast block-matching algorithm based on the normalized cross-correlation, where the elimination order is determined based on the gradient magnitudes of subblocks in the current macroblock. Multilevel Cauchy-Schwartz inequality is derived to skip unnecessary block-matching calculations in the proposed algorithm. Also, additional complexity reduction is achieved re-using the normalized cross correlation values for the spatially neighboring macroblock because the search areas of adjacent macroblocks are overlapped. Simulation results show that the proposed algorithm can improve the speed-up ratio up to about 3 times in comparison with the existing algorithm.

• Communications for Statistical Applications and Methods
• /
• v.18 no.2
• /
• pp.189-199
• /
• 2011

In this paper, we develop the noninformative priors for the common intraclass correlation coefficient when independent samples drawn from multivariate normal populations. We derive the first and second order matching priors. We reveal that the second order matching prior dose not match alternative coverage probabilities up to the second order and is not a HPD matching prior. It turns out that among all of the reference priors, one-at-a-time reference prior satisfies a second order matching criterion. Our simulation study indicates that one-at-a-time reference prior performs better than the other reference priors in terms of matching the target coverage probabilities in a frequentist sense.

• Spatial Information Research
• /
• v.15 no.2
• /
• pp.181-187
• /
• 2007

To make digital terrain data, automatic correlation matching by stereo airborne/satellite images has been researched. The result of automatic correlation matching has a limit on extracting exact ground height because of angle of sensor, tree of height. Therefore, the amount of editing works depend on the distribution of spatial feature in images as well as image quality. This paper shows that the automatic correlation matching result was affected by density and height of tree.

• Korean Journal of Remote Sensing
• /
• v.25 no.3
• /
• pp.263-270
• /
• 2009

Noise band removal is a crucial step before spectral matching since the noise bands can distort the typical shape of spectral reflectance, leading to degradation on the matching results. This paper proposes a statistical noise band removal method for hyperspectral data using the correlation coefficient between two bands. The correlation coefficient measures the strength and direction of a linear relationship between two random variables. Considering each band of the hyperspectral data as a random variable, the correlation between two signal bands is high; existence of a noisy band will produce a low correlation due to ill-correlativeness and undirected ness. The unsupervised k-nearest neighbor clustering method is implemented in accordance with three well-accepted spectral matching measures, namely ED, SAM and SID in order to evaluate the validation of the proposed method. This paper also proposes a hierarchical scheme of combining those measures. Finally, a separability assessment based on the between-class and the within-class scatter matrices is followed to evaluate the applicability of the proposed noise band removal method. Also, the paper brings out a comparison for spectral matching measures. The experimental results conducted on a 228-band hyperspectral data show that while the SAM measure is rather resistant, the performance of SID measure is more sensitive to noise.

• Journal of Communications and Networks
• /
• v.7 no.3
• /
• pp.278-283
• /
• 2005

This paper proposes a blind channel estimation scheme for long code direct sequence code division multiple access (DS­CDMA) systems with multipath fading channels. This scheme combines the advantages of Toeplitz displacement and correlation matching methods to achieve improved performance. The basic idea is to remove the effects of noise and interferences with Toeplitz displacement operation and then estimate the multi path channel parameters with the correlation matching method. Simulation results are presented to show that the proposed scheme provides better MSE performance and robustness against the near-far problem.

• Journal of the Korean Statistical Society
• /
• v.36 no.1
• /
• pp.77-91
• /
• 2007

This paper considers development of noninformative priors for the familial data when the families have equal number of offspring. Several noninformative priors including the widely used Jeffreys' prior as well as the different reference priors are derived. Also, a simultaneously-marginally-probability-matching prior is considered and probability matching priors are derived when the parameter of interest is inter- or intra-class correlation coefficient. The simulation study implemented by Gibbs sampler shows that two-group reference prior is slightly edge over the others in terms of coverage probability.