• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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• pp.53-56
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• 2008

Generally, the quality of satellite images is expressed by GSD (Ground Sample Distance), MTF (Modulation Transfer Function) and SNR (Signal to Noise Ratio). However, these factors are technology-oriented and do not explain interpretability of satellite images. We need a standardized index which shows standard of interpretability. In this study, we estimated NIIRS (National Imagery Interpretability Rating Scale) through the GIQE (General Image Quality Equation) which is able to judge image interpretability with the standardized index. Traditionally, NIIRS has been determined manually by specialized image analysts. We used the GIQE in order to reduce inefficiency and high costs cause by manual interpretation and to produce accurate NIIRS. For monitoring image degradation, we estimated GIQE physical parameters from image analysis and carried out time series analysis about the quality of the KOMPSAT-1 images. On all of the tests, we were able to identify the image degradation due to the changing time. This indicates that NIIRS derived from GIQE will be used for image degradation indicator.

• 대한원격탐사학회지
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• 제27권5호
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• pp.587-599
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• 2011

NIIRS(National Imagery Interpretability Rating Scale)는 영상의 판독력을 설명하는 품질 지표로 고해상도 위성영상의 품질을 나타내는데 널리 사용되어 왔다. 이는 MTF(Modulation Transfer Function), SNR(Signal to Noise Ratio), 또는 GSD(Ground Sampling Distance)와는 달리 객관적이고, 직관적으로 영상의 전반적인 품질을 설명할 수 있다는 점에서, 그 활용도가 매우 크다고 할 수 있다. NIIRS는 전문 판독가에 의해 육안으로 직접 측정되거나, 영상의 에지 분석(Edge analysis)을 통해 정확하게 추정할 수 있다. 일반적으로 에지 분석에는 품질 측정을 위해 특별히 제작된 인공의 표적이 사용된다. 이 인공표적의 일례로 특정 크기의 반사율 차이를 가지는 흑백 패턴의 천막 형태가 있으며, 이러한 인공표적은 인공위성의 촬영경로 상에 설치되어 진다. 이 때문에 인공표적을 이용하는 방식은 표적의 설치와 관련하여 많은 비용이 지출될 뿐 아니라, 수시로 수행될 수 없다는 문제점을 가지게 된다. 이에 본 논문에서는 영상에서 쉽게 관측될 수 있는 자연표적들로부터 정확한 NIIRS 추정이 가능한 새로운 방식의 에지 분석법을 제안하였다. 이 방법은 임의의 성질을 가지는 자연표적의 특성을 반영하기 위해 알고리즘의 강인성이 강조되었으며, 다양한 실험들을 통해 성능이 평가되었다. 실험 결과는 제안 알고리즘이 기존 방식의 대안으로서 충분히 활용 가능함을 보여 주었다.

• 한국멀티미디어학회논문지
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• 제19권4호
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• pp.725-735
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• 2016

High-resolution satellite images are used in the fields of mapping, natural disaster forecasting, agriculture, ocean-based industries, infrastructure, and environment, and there is a progressive increase in the development and demand for the applications of high-resolution satellite images. Users of the satellite images desire accurate quality of the provided satellite images. Moreover, the distinguishability of each image captured by an actual satellite varies according to the atmospheric environment and solar angle at the captured region, the satellite velocity and capture angle, and the system noise. Hence , NIIRS must be measured for all captured images. There is a significant deficiency in professional human resources and time resources available to measure the NIIRS of few hundred images that are transmitted daily. Currently, NIIRS is measured every few months or even few years to assess the aging of the satellite as well as to verify and calibrate it [3]. Therefore, we develop an algorithm that can measure the national image interpretability rating scales (NIIRS) of a typical satellite image rather than an artificial target satellite image, in order to automatically assess its quality. In this study, the criteria for automatic edge region extraction are derived based on the previous works on manual edge region extraction [4][5], and consequently, we propose an algorithm that can extract the edge region. Moreover, RER and H are calculated from the extracted edge region for automatic edge region extraction. The average NIIRS value was measured to be 3.6342±0.15321 (2 standard deviations) from the automatic measurement experiment on a typical satellite image, which is similar to the result extracted from the artificial target.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1615-1615
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• 2001

During the past ten years, Near Infrared Spectroscopy has been successfully applied to the analysis of a great variety of agriculture products. Previous works (Morra et al., 1991; Salgo et al., 1998) have shown the potential of this technology for soil analysis, estimating different parameters just with one single scan. The main advantages of NIR applications in soils are the speed of response, allowing the increase of the number of samples analysed to define a particular soil, and the instantaneous elaboration of recommendations for fertilization and soil amendment. Another advantage is to avoid the use of chemical reagents at all, being an environmentally safe technique. In this paper, we have studied a set of 129 soil samples selected from representative glasshouse soils from Southern Spain. The samples were dried, milled, and sieved to pass a 2 mm sieve and then analysed for organic carbon, total nitrogen, inorganic nitrogen (nitrate ammonium), hygroscopic humidity, pH and electrical conductivity in the 1:1 extract. NIR spectra of all samples were obtained in reflectance mode using a Foss NIR Systems 6500 spectrophotometer equipped with a spinning module. Calibration equations were developed for seven analytical parameters (ph, Total nitrogen, organic nitrogen, organic carbon, C/N ratio and Electric Conductivity). Preliminary results show good correlation coefficients and standard errors of cross validation in equations obtained for Organic Carbon, Organic Nitrogen, Total Nitrogen and C/N ratio. Calibrations for nitrates and nitrites, ammonia and electric conductivity were not acceptable. Calibration obtained for pH had an acceptable SECV, but the determination coefficient was found very poor probably due to the reduced range in reference values. Since the estimation of Organic Carbon and C/N ratio are acceptable NIIRS could be used as a fast method to assess the necessity of organic amendments in soils from Mediterranean regions where the low level of organic matter in soils constitutes an important agronomic problem. Furthermore, the possibility of a single and fast estimation of Total Nitrogen (tedious determination by modifications of the Kjeldahl procedure) could provide and interesting data to use in the estimation of nitrogen fertilizer rates by means of nitrogen balances.