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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
> Journal Vol & Issue
Korean Journal of Remote Sensing
Journal Basic Information
Journal DOI :
The Korean Society of Remote Sensing
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Volume & Issues
Volume 25, Issue 6 - Dec 2009
Volume 25, Issue 5 - Oct 2009
Volume 25, Issue 4 - Aug 2009
Volume 25, Issue 3 - Jun 2009
Volume 25, Issue 2 - Apr 2009
Volume 25, Issue 1 - Feb 2009
Selecting the target year
Stereoscopic 3D Modelling Approach with KOMPSAT-2 Satellite Data
Tserennadmid, T. ; Kim, Tae-Jung ;
Korean Journal of Remote Sensing, volume 25, issue 3, 2009, Pages 205~214
This paper investigates stereo 3D viewing for linear pushbroom satellite images using the Orbit-Attitude Model proposed by Kim (2006) and using OpenGL graphic library in Digital Photogrammetry Workstation. 3D viewing is tested with KOMPSAT-2 satellite stereo images, a large number of GCPs (Ground control points) collected by GPS surveying and orbit-attitude sensor model as a rigorous sensor model. Comparison is carried out by two accuracy measurements: the accuracy of orbit-attitude modeling with bundle adjustment and accuracy analysis of errors in x and y parallaxes. This research result will help to understand the nature of 3D objects for high resolution satellite images, and we will be able to measure accurate 3D object space coordinates in virtual or real 3D environment.
Wavelet Pair Noise Removal for Increasing the Classification Accuracy of a Remotely Sensed Image
Jin, Hong-Sung ; Yoo, Hee-Young ; Eom, Joo-Young ; Choi, II-Su ; Han, Dong-Yeob ;
Korean Journal of Remote Sensing, volume 25, issue 3, 2009, Pages 215~223
The noise removal as a preprocessing was tried with various kinds of wavelet pairs. Wavelet transform for 2D images generally uses the same wavelets as basis functions in horizontal and vertical directions. A method with different wavelets was tried for each direction separately, which gives more precise interpretation of the classification. Total 486 pairs of wavelets from nine basis functions were tried to remove image noises. The classification accuracies before and after the noise removal were compared. Although all kinds of wavelet pairs showed the increased accuracies in classification, there were best and worst wavelet pairs depending on the data sets. Wavelet pairs with low energy percentage of LL band showed the high classification accuracy. A pattern was found in the results that very similar vertical accuracy was distributed for each horizontal ones. Since Haar is the shortest length filter, Haar could be a predictor wavelet to find the good wavelet pairs.
Comparisons of the Environmental Characteristics of Intertidal Beach and Mudflat
Kim, Tae-Rim ;
Korean Journal of Remote Sensing, volume 25, issue 3, 2009, Pages 225~231
The characteristics of morphological shapes, wave heights, tidal ranges and sediment sizes are observed and compared between intertidal beach and mudflat. The Mohang sand beach, southwest coast of Korea, is located just next to the large mudflat and has tidal range over 5 meters. Wave measurements are conducted at each entrance of the beach and mudflat as well as at the outside waters representing the incident waves to these different coastal environments. The morphological characteristics are also examined including the sediment size and the slope of the bathymetry, For the observation of morphological shapes, camera monitoring technique is used to measure the spatial information of intertidal bathymetry. The water lines moving on the intertidal flat/beach durinq a flood indicate depth contours between low and high water lines. The water lines extracted from the consecutive images are rectified to get the ground coordinates of each depth contours and integrated to provide three dimensional information of intertidal topography. The wave data show that sand beach is in the condition of severer wave forcing but tidal range is almost identical in both environment. The slope of the mudflat is much milder than the sand beach with finer sediment.
Support Vector Machine and Spectral Angle Mapper Classifications of High Resolution Hyper Spectral Aerial Image
Enkhbaatar, Lkhagva ; Jayakumar, S. ; Heo, Joon ;
Korean Journal of Remote Sensing, volume 25, issue 3, 2009, Pages 233~242
This paper presents two different types of supervised classifiers such as support vector machine (SVM) and spectral angle mapper (SAM). The Compact Airborne Spectrographic Imager (CASI) high resolution aerial image was classified with the above two classifier. The image was classified into eight land use /land cover classes. Accuracy assessment and Kappa statistics were estimated for SVM and SAM separately. The overall classification accuracy and Kappa statistics value of the SAM were 69.0% and 0.62 respectively, which were higher than those of SVM (62.5%, 0.54).
Wind Retrieval from X-band SAR Image Using Numerical Ocean Scattering Model
Kim, Duk-Jin ;
Korean Journal of Remote Sensing, volume 25, issue 3, 2009, Pages 243~253
For the last 14 years, space-borne satellite SAR system such as RADARSAT-1, ERS-2, and ENVISAT ASAR have provided a continuous observation over the ocean. However, the data acquired from those systems were limited to C-band frequency until the advent of the first spacebome German X-band SAR system TerraSAR-X in 2007. Korea is also planning to launch the nation's first X-band SAR satellite (KOMPSAT-5) in 2010. It is timely and necessary to develop X-band models for estimating geophysical parameters from these X-band SAR systems. In this study, X-band wind retrieval model was investigated and developed based on numerical ocean scattering model (radar backscattering model and hydrodynamic interaction model). Although these models have not yet been tested and validated for broad ranges of wind conditions, the estimated wind speeds from TerraSAR-X data show generally good agreement with in-situ measurements.
New Unsupervised Classification Technique for Polarimetric SAR Images
Oh, Yi-Sok ; Lee, Kyung-Yup ; Jang, Ge-Ba ;
Korean Journal of Remote Sensing, volume 25, issue 3, 2009, Pages 255~261
A new polarimetric SAR image classification technique based on the degree of polarization (DoP) and the co-polarized phase-difference (CPD) is presented in this paper. Since the DoP and the CPD of a scattered wave provide information on the randomness of the scattering and the type of scattering mechanisms, at first, the statistics of the DoP and CPD are examined with measured polarimetric SAR image data. Then, a DoP-CPD diagram with appropriate boundaries between six different classes is developed based on the SAR image. The classification technique is verified using the JPL AirSAR and ALOS PALSAR polarimetric data. The technique may have capability to classify an SAR image into six major classes; a bare surface, a village, a crown-layer short vegetation canopy, a trunk-layer short vegetation canopy, a crown-layer forest, and a trunk-dominated forest.
Noisy Band Removal Using Band Correlation in Hyperspectral lmages
Huan, Nguyen Van ; Kim, Hak-Il ;
Korean Journal of Remote Sensing, volume 25, issue 3, 2009, Pages 263~270
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.
Application of Multiple Threshold Values for Accuracy Improvement of an Automated Binary Change Detection Model
Yu, Byeong-Hyeok ; Chi, Kwang-Hoon ;
Korean Journal of Remote Sensing, volume 25, issue 3, 2009, Pages 271~285
Multi-temporal satellite imagery can be changed into a transform image that emphasizes the changed area only through the application of various change detection techniques. From the transform image, an automated change detection model calculates the optimal threshold value for classifying the changed and unchanged areas. However, the model can cause undesirable results when the histogram of the transform image is unbalanced. This is because the model uses a single threshold value in which the sign is either positive or negative and its value is constant (e.g. -1, 1), regardless of the imbalance between changed pixels. This paper proposes an advanced method that can improve accuracy by applying separate threshold values according to the increased or decreased range of the changed pixels. It applies multiple threshold values based on the cumulative producer's and user's accuracies in the automated binary change detection model, and the analyst can automatically extract more accurate optimal threshold values. Multi-temporal IKONOS satellite imagery for the Daejeon area was used to test the proposed method. A total of 16 transformation results were applied to the two study sites, and optimal threshold values were determined using accuracy assessment curves. The experiment showed that the accuracy of most transform images is improved by applying multiple threshold values. The proposed method is expected to be used in various study fields, such as detection of illegal urban building, detection of the damaged area in a disaster, etc.
Image Registration for Cloudy KOMPSAT-2 Imagery Using Disparity Clustering
Kim, Tae-Young ; Choi, Myung-Jin ;
Korean Journal of Remote Sensing, volume 25, issue 3, 2009, Pages 287~294
KOMPSAT-2 like other high-resolution satellites has the time and angle difference in the acquisition of the panchromatic (PAN) and multispectral (MS) images because the imaging systems have the offset of the charge coupled device combination in the focal plane. Due to the differences, high altitude and moving objects, such as clouds, have a different position between the PAN and MS images. Therefore, a mis-registration between the PAN and MS images occurs when a registration algorithm extracted matching points from these cloud objects. To overcome this problem, we proposed a new registration method. The main idea is to discard the matching points extracted from cloud boundaries by using an automatic thresholding technique and a classification technique on a distance disparity map of the matching points. The experimental result demonstrates the accuracy of the proposed method at ground region around cloud objects is higher than a general method which does not consider cloud objects. To evaluate the proposed method, we use KOMPSAT-2 cloudy images.
Boundary-adaptive Despeckling : Simulation Study
Lee, Sang-Hoon ;
Korean Journal of Remote Sensing, volume 25, issue 3, 2009, Pages 295~309
In this study, an iterative maximum a posteriori (MAP) approach using a Bayesian model of Markovrandom field (MRF) was proposed for despeckling images that contains speckle. Image process is assumed to combine the random fields associated with the observed intensity process and the image texture process respectively. The objective measure for determining the optimal restoration of this "double compound stochastic" image process is based on Bayes' theorem, and the MAP estimation employs the Point-Jacobian iteration to obtain the optimal solution. In the proposed algorithm, MRF is used to quantify the spatial interaction probabilistically, that is, to provide a type of prior information on the image texture and the neighbor window of any size is defined for contextual information on a local region. However, the window of a certain size would result in using wrong information for the estimation from adjacent regions with different characteristics at the pixels close to or on boundary. To overcome this problem, the new method is designed to use less information from more distant neighbors as the pixel is closer to boundary. It can reduce the possibility to involve the pixel values of adjacent region with different characteristics. The proximity to boundary is estimated using a non-uniformity measurement based on standard deviation of local region. The new scheme has been extensively evaluated using simulation data, and the experimental results show a considerable improvement in despeckling the images that contain speckle.