• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1135-1147
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• 2021

In order to geometrically correct high-resolution satellite imagery, the sensor modeling process that restores the geometric relationship between the satellite sensor and the ground surface at the image acquisition time is required. In general, high-resolution satellites provide RPC (Rational Polynomial Coefficient) information, but the vendor-provided RPC includes geometric distortion caused by the position and orientation of the satellite sensor. GCP (Ground Control Point) is generally used to correct the RPC errors. The representative method of acquiring GCP is field survey to obtain accurate ground coordinates. However, it is difficult to find the GCP in the satellite image due to the quality of the image, land cover change, relief displacement, etc. By using image maps acquired from various sensors as reference data, it is possible to automate the collection of GCP through the image matching algorithm. In this study, the RPC of KOMPSAT-3A satellite image was corrected through the extracted matching point using the UAV (Unmanned Aerial Vehichle) imagery. We propose a pre-porocessing method for the extraction of matching points between the UAV imagery and KOMPSAT-3A satellite image. To this end, the characteristics of matching points extracted by independently applying the SURF (Speeded-Up Robust Features) and the phase correlation, which are representative feature-based matching method and area-based matching method, respectively, were compared. The RPC adjustment parameters were calculated using the matching points extracted through each algorithm. In order to verify the performance and usability of the proposed method, it was compared with the GCP-based RPC correction result. The GCP-based method showed an improvement of correction accuracy by 2.14 pixels for the sample and 5.43 pixelsfor the line compared to the vendor-provided RPC. In the proposed method using SURF and phase correlation methods, the accuracy of sample was improved by 0.83 pixels and 1.49 pixels, and that of line wasimproved by 4.81 pixels and 5.19 pixels, respectively, compared to the vendor-provided RPC. Through the experimental results, the proposed method using the UAV imagery presented the possibility as an alternative to the GCP-based method for the RPC correction.

• Journal of KIISE:Software and Applications
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• v.28 no.7
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• pp.501-510
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• 2001

Generally, it is essential to estimate exact disparity for the 3D modeling from stereo images. Because existing methods calculate disparities from a whole image, they require too much cimputational time and bring about the mismatching problem. In this article, using the characteristic that the disparity vectors in stereo images are distributed not equally in a whole image but only exist about the background and obhect, we do a wavelet transformation on stereo images and estimate coarse disparity fields from the reduced lowpass field using area-based method at first-step. From these coarse disparity vectors, we generate disparity histogram and then separate object from background area using it. Afterwards, we restore only object area to the original image and estimate dense and accurate disparity by our two-step pixel-based method which does not use pixel brightness but use second gradient. We also extract feature points from the separated object area and estimate depth information by applying disparity vectors and camera parameters. Finally, we generate 3D model using both feature points and their z coordinates. By using our proposed, we can considerably reduce the computation time and estimate the precise disparity through the additional pixel-based method using LOG filter. Furthermore, our proposed foreground/background method can solve the mismatching problem of existing Delaunay triangulation and generate accurate 3D model.

• Journal of the Korean Society of Food Science and Nutrition
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• v.37 no.1
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• pp.109-116
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• 2008

In this study, the breads with medicinal herbs (MH) composites showing immunostimulating activity were prepared and their characteristics were examined. Fourteen kinds of medicinal herbs were extracted with hot water and divided into 3 groups (MH-1, MH-2, MH-3) based on their contents. All groups showed immunostimulating activity in terms of macrophage phagocytosis, nitrite production, cytostatic activity and cytokine production. In the preparation of breads containing MH extracts of various contents (0, 30, 50, 70, and 100%), there was no significant difference among dough pHs of all groups after first fermentation, but loaf volume was significantly (p<0.05) increased in 70% added group while decreased in 30%, 50%, and 100% added groups compared to the control. The "a" and "b" values of bread crumb increased with the content of MH extracts while "L" value decreased, but these values of bread crust were similar to the control group. Most improvements in hardness, adhesiveness, gumminess and chewiness of bread were noticed by the addition of 70% MH extracts, but those of springiness, cohesiveness and resilience were mostly by the 50% addition ones. Through the sensory evaluation, it was revealed that mouth feeling, taste and overall preference decreased at breads containing 70% and 100% extracts, although appearance and crumb texture were not significantly (p<0.05) different among all groups.