• 한국농공학회:학술대회논문집
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• 한국농공학회 1999년도 Proceedings of the 1999 Annual Conference The Korean Society of Agricutural Engineers
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• pp.765-770
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• 1999

The purpose of this study is to obtain land classification map by using remotely sensed data; Landsat TM and SPOT panchromatic, and to compare their results with statistical data and digitized coverage from topographic paper map. The classification was conducted by maximum likelihood method with training sets. The best result was obtained from the Landsat TM merged by SPOT Panchromatic, that is, similar with statistical data. This is caused by setting more precise training sets with the enhanced spatial resolution by using SPOT Panchromatic. The classified map may be useful as a fundamental data to estimate pollutant load in regional scale of agricultural watershed.

• 한국측량학회지
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• 제36권5호
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• pp.413-422
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• 2018

Many applications using satellite data from high-resolution multispectral sensors require an image fusion step, known as pansharpening, before processing and analyzing the multispectral images when spatial fidelity is crucial. Image fusion methods are to improve images with higher spatial and spectral resolutions by reducing spectral distortion, which occurs on image fusion processing. The image fusion methods can be classified into MRA (Multi-Resolution Analysis) and CSA (Component Substitution Analysis) approaches. To suggest the efficient image fusion method for Pleiades and KOMPSAT (Korea Multi-Purpose Satellite) 3 satellites, this study will evaluate image fusion methods for multispectral and panchromatic images. HPF (High-Pass Filtering), SFIM (Smoothing Filter-based Intensity Modulation), GS (Gram Schmidt), and GSA (Adoptive GS) were selected for MRA and CSA based image fusion methods and applied on multispectral and panchromatic images. Their performances were evaluated using visual and quality index analysis. HPF and SFIM fusion results presented low performance of spatial details. GS and GSA fusion results had enhanced spatial information closer to panchromatic images, but GS produced more spectral distortions on urban structures. This study presented that GSA was effective to improve spatial resolution of multispectral images from Pleiades 1A and KOMPSAT 3.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2007년도 춘계학술발표회 논문집
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• pp.207-210
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• 2007

본 연구에서는 고해상도의 IKONOS panchromatic 영상과 multispectral 영상을 IHS와 PCA 방법으로 중합하고 그 결과를 비교하였다. 평가에 있어서는 중합된 영상들과 원영상간의 필셀 값에 대한 평균제곱근오차를 구하고 그 결과를 분석하였다. 분석 결과, multispectral band 1, 3, 4를 사용하는 IHS 방법, multispectral band 1, 2, 4를 사용하는 IHS 방법 및 multispectral band 1, 3, 4를 사용하는 PCA 방법이 원영상의 특성을 잘 보존하는 것으로 평가되었다.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송∙미디어공학회 2018년도 하계학술대회
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• pp.185-187
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• 2018

This paper presents an aircraft detection on panchromatic image using densely connected convolutional network. This algorithm connects all preceding feature-maps to all subsequent layers. It is encouraged to reuse feature-maps and enhance feature-maps representation. This algorithm is driven to learn aircraft feature to detect aircraft objects on panchromatic imagery. Based on the experimental result, it can yield accuracy of 92%.

• 대한원격탐사학회지
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• 제24권3호
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• pp.257-266
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• 2008

This study presents an approach to synthesize multispectral images at a higher resolution by exploiting a high-resolution image acquired in panchromatic modality. The synthesized images should be similar to the multispectral images that would have been observed by the corresponding sensor at the same high resolution. The proposed scheme is designed to reconstruct the multispectral images at the higher resolution with as less color distortion as possible. It uses a regression model of the second order to fit panchromatic data to multispectral observations. Based on the regression model, the multispectral images at the higher spatial resolution of the panchromatic image are optimized by a quadratic programming. In this study, the new method was applied to the IKONOS 1m panchromatic and 4m multispectral data, and the results were compared with them of several current approaches. Experimental results demonstrate that the proposed scheme can achieve significant improvement over other methods.

• 대한원격탐사학회지
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• 제24권5호
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• pp.525-533
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• 2008

This study presents a pansharpening method, so called FitPAN, to synthesize multispectral images at a higher resolution by exploiting a high-resolution image acquired in panchromatic modality. FitPAN is a modified version of the quadratic programming approach proposed in (Lee, 2008), which is designed to generate synthesized multispectral images similar to the multispectral images that would have been observed by the corresponding sensor at the same high resolution. The proposed scheme aims at reconstructing the multispectral images at the higher resolution with as less spectral distortion as possible. This study also proposes a sharpening process to eliminate some distortions appeared in the fused image of the higher resolution. It employs the Point-Jacobian MAP iteration utilizing the contextual information of the original panchromatic image. In this study, the new method was applied to the IKONOS 1m panchromatic and 4m multispectral data, and the results were compared with them of several current approaches. Experimental results demonstrate that the proposed scheme can achieve significant improvement in both spectral and block distortion.

• 한국지리정보학회지
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• 제5권4호
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• pp.86-92
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• 2002

고해상도 위성 IRS-1C의 Panchromatic 영상 자료를 이용하여 한국 근해에서 선박의 수와 위치를 파악할 수 있는 가능성을 살펴보았다. Panchromatic 위성 영상에서 선박과 주변환경에 대한 위치, 크기, 모양, 그림자, 색조, 질감 및 모양의 공간배열, 높이와 깊이, 현황 및 연관성 등의 영상해석 요소를 활용하여 선박 모니터링의 논리적 접근기법을 연구하였다. 선박의 공간적 위치는 GCP가 없는 해상에서 영상의 중심위치 정보로부터 반경 35km내에서 지구좌표점으로 전환하였다. 선박의 크기는 선수에서 선미까지이나 선미에서 생기는 종파(following wave)와 추정 구분하여야 했다. 길이 100m를 기준으로 연근해 어선과 상선으로 구분하였다. 선박의 모양은 종파의 영향으로 영상에서 유선형이었다. 작은 구름의 경우 선박의 모양과 유사했으나, 해상에 반영된 구름의 그림자로 배와 구분할 수 있었다. 색조는 바다표면이 검은색을 띤 반면 소형선박은 밝은 흰색으로 나타났다. 바다의 거친 정도와 파도의 방향성 배열 등을 통해 파도와 선박을 구분하였다. 또한 쌍끌이 어선과 같은 조업방법이 어선의 어업별 종류를 영상에서 추정하는데 용이한 기초 연관 자료가 되었다.

• 대한원격탐사학회지
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• 제26권4호
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• pp.439-449
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• 2010

이 논문에서는 KOMPSAT-2 스테레오 영상의 PAN밴드에 존재하는 미세한 크기의 Y시차가 발생하는 원인을 규명하고 이를 개선하기 위한 일련의 실험 및 분석과정을 보고한다. 분석결과, Y시차가 발생하는 원인이 KOMPSAT-2 영상을 생성할 때 PAN밴드를 MS밴드와 일치하도록 Warping처리하는 과정에서 발생한 Resampling 오차 때문인 것으로 판단할 수 있었다. 또한 엄밀한 PAN밴드의 Warping 방식을 적용하여 Resampling 오차를 제거함으로써 Y 시차문제가 상당부분 개선될 수 있음을 확인하였다. 또한 KOMPSAT-2 영상 PAN밴드에서 관측된 밝기값 밀림현상도 엄밀한 Warping처리를 통해서 개선될 수 있음을 확인하였다. 따라서, 보다 엄밀한 Warping기법이 KOMPSAT-2 영상처리과정에 적용될 수 있다면 KOMPSAT-2 영상의 기하정확도 및 복사정확도가 많이 개선될 수 있을 것으로 기대한다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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• pp.792-797
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• 2002

In the following paper two algorithms, suitable for the analysis of panchromatic data as provided by KOMPSAT-1 will be presented. One is a texture analysis which will be used to create a settlement mask based on the variations of gray values. The other is a fusion algorithm which allows the combination of high resolution panchromatic data with medium resolution multispectral data. The procedure developed for this purpose uses the spatial information present in the high resolution image to spatially enhance the low resolution image, while keeping the distortion of the multispectral information to a minimum. This makes it possible to use the fusion results for standard multispecatral classification routines. The procedures presented here can be automated to large extent, making them suitable for a standard processing routine of satellite data.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.485-487
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• 2003

Independent Component Analysis (ICA) is used to generate ICA filter for computing feature vector for image window. Filters that have high discrimination power are selected to classify image from these ICA filters. Proposed classification algorithm is based on probability distribution of feature vector.