• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.125-127
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• 2004

High-resolution satellite images offer abundance information of the earth surface for remote sensing applications. The information includes geometry, texture and attribute characteristic. The pixel-based image classification can't satisfy high-resolution satellite image's classification precision and produce large data redundancy. Object-oriented information extraction not only depends on spectrum character, but also use geometry and structure information. It can provide an accessible and truly revolutionary approach. Using Beijing Spot 5 high-resolution image and object-oriented classification with the eCognition software, we accomplish the cultures' precise classification. The test areas have five culture types including water, vegetation, road, building and bare lands. We use nearest neighbor classification and appraise the overall classification accuracy. The average of five species reaches 0.90. All of maximum is 1. The standard deviation is less than 0.11. The overall accuracy can reach $95.47\%.$ This method offers a new technology for high-resolution satellite images' available applications in remote sensing culture classification.

• 지구물리와물리탐사
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• 제14권4호
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• pp.335-341
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• 2011

탐사 시스템을 포함하여 대부분의 센싱 및 계측 시스템은 중요한 정보를 놓치지 않기 위하여 필요한 정보 보다 높은 샘플주기로 정보를 수집 한다. 이는 경우에 따라 센싱 및 계측 시스템이 비효율적일 수 있음을 의미한다. 본 논문에서는 적은 샘플자료로부터 높은 정밀도의 정보 취득에 관한 새로운 두 가지 연구분야를 소개하고자 한다. 하나는 가능한 적은 샘플로 원래의 정보를 복원하는 압축센싱(Compressed Sensing)기술이며, 또 다른 하나는 이미 얻어진 한정된 샘플로부터 높은 해상도의 정보를 추정하는 초고해상도(Super-Resolution)기술이다. 본 논문에서는 압축센싱 기술의 기본이론과 복원기술에 대해 설명하고, 탐사분야의 적용 사례, 초고해상도 기술의 배경 및 최근의 기술인 FRI (Finite Rate of Innovation) 개념과 LIMS (Least-squares based Iterative Multipath Super-resolution)기술의 적용사례를 소개한다. 결론으로는 이러한 새로운 기술들이 지구물리 탐사분야에 어떻게 활용될 수 있는지 논의한다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.525-527
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• 2003

Recently, the spatial resolution of earth observation satellites is significantly increased to a few meters. Such high spatial resolution images definitely will provide lots of information for detail-thirsty remote sensing users. However, it is more difficult to develop automated image algorithms for automated image feature extraction and pattern recognition. In this study, we propose a two-stage procedure to extract road information from high resolution satellite images. At first stage, a watershed segmentation technique is developed to classify the image into various regions. Then, a knowledge is built for road and used to extract the road regions. In this study, we use panchromatic and multi-spectral images of the IKONOS satellite as test dataset. The experiment result shows that the proposed technique can generate suitable and meaningful road objects from high spatial resolution satellite images. Apparently, misclassified regions such as parking lots are recognized as road needed further refinement in future research.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.1319-1322
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• 2003

According to the evolutive theory of saline, combined with field survey data, the authors have discussed the theoretical model of recording past climatic change of Luobupo saline. After interpreted and analyzed the causes of the ringy image, the authors have mapped high resolution climatic changing graph of Luobupo saline during past 2000 years by using remote sensing method. Contrast to the known results, it is proved that the research results have comparability and continuity. The resolution of special climatic event can reach in one year, and in general, the resolution of climatic change can reach in ten to twenty years.

• IEIE Transactions on Smart Processing and Computing
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• 제3권1호
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• pp.19-27
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• 2014

Compressive sensing is an emerging sampling technique which enables sampling a signal at a much lower rate than the Nyquist rate. In this paper, we propose a novel framework based on Kronecker compressive sensing that provides multi-resolution image reconstruction capability. By exploiting the relationship of the sensing matrices between low and high resolution images, the proposed method can reconstruct both high and low resolution images from a single measurement vector. Furthermore, post-processing using BM3D improves its recovery performance. The experimental results showed that the proposed scheme provides significant gains over the conventional framework with respect to the objective and subjective qualities.

• 대한원격탐사학회지
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• 제39권4호
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• pp.459-466
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• 2023

In the last decade, artificial intelligence's dramatic advancement with the development of various deep learning techniques has significantly contributed to remote sensing fields and satellite image applications. Among many prominent areas, super-resolution research has seen substantial growth with the release of several benchmark datasets and the rise of generative adversarial network-based studies. However, most previously published remote sensing benchmark datasets represent spatial resolution within approximately 10 meters, imposing limitations when directly applying for super-resolution of small objects with cm unit spatial resolution. Furthermore, if the dataset lacks a global spatial distribution and is specialized in particular land covers, the consequent lack of feature diversity can directly impact the quantitative performance and prevent the formation of robust foundation models. To overcome these issues, this paper proposes a method to generate benchmark datasets by simulating the modulation transfer functions of the sensor. The proposed approach leverages the simulation method with a solid theoretical foundation, notably recognized in image fusion. Additionally, the generated benchmark dataset is applied to state-of-the-art super-resolution base models for quantitative and visual analysis and discusses the shortcomings of the existing datasets. Through these efforts, we anticipate that the proposed benchmark dataset will facilitate various super-resolution research shortly in Korea.

• 대한원격탐사학회지
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• 제22권5호
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• pp.337-350
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• 2006

The characteristics of neighborhood correlation images for change detection were explored at different spatial resolution scales. Bi-temporal QuickBird datasets of Las Vegas, NV were used for the high spatial resolution image analysis, while bi-temporal Landsat $TM/ETM^{+}$ datasets of Suwon, South Korea were used for the mid spatial resolution analysis. The neighborhood correlation images consisting of three variables (correlation, slope, and intercept) were evaluated and compared between the two scales for change detection. The neighborhood correlation images created using the Landsat datasets resulted in somewhat different patterns from those using the QuickBird high spatial resolution imagery due to several reasons such as the impact of mixed pixels. Then, automated binary change detection was also performed using the single and multiple neighborhood correlation image variables for both spatial resolution image scales.

• 전자공학회논문지
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• 제52권10호
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• pp.118-128
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• 2015

압축센싱 기술이 직면하고 있는 두 가지의 도전과제는 복원 알고리즘의 연산 복잡도 개선과 부호화 효율 향상 문제이다. 이에 대한 해결방안으로, 본 논문은 최대 3 가지의 공간 해상도 조절 및 향상된 압축센싱 부호화 성능을 가능하게 하는 공간 스케일러블 Kronecker 압축센싱 구조를 제안한다. 제안 방법의 기저 계층(base layer)에서는 quincunx 샘플링 격자에 기반 하는 듀얼-해상도 센싱 행렬을 사용한다. 해당 센싱 행렬은 낮은 해상도의 영상에 대한 고속-프리뷰(preview) 기능을 가능케 한다. 향상 계층(enhancement layer)에서는 획득한 측정값과 예측 측정값 간의 잔차 측정값을 부호화 한다. 복원과정에서는 기저 계층으로부터 낮은 해상도의 복원 영상을 획득 할 수 있는 반면, 두 개의 계층을 모두 사용하여 복원하는 경우 높은 해상도의 영상을 획득할 수 있다. 실험 결과, 제안하는 구조가 종래의 단일 계층방법 및 다중-해상도 기반 구조에 비해, 2.0bpp일 때 PSNR 성능이 각각 5.75dB 및 5.05dB 더 향상됨을 확인하였다.

• 대한원격탐사학회지
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• 제19권5호
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• pp.393-402
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• 2003

In times of the civil uses of commercialized high-resolution satellite imagery, applications of remote sensing have been widely extended to the new fields or the problem solving beyond traditional application domains. Transportation application of this sensor data, related to the automatic or semiautomatic road extraction, is regarded as one of the important issues in uses of remote sensing imagery. Related to these trends, this study focuses on automatic road extraction using Gradient Direction Profile Algorithm (GDPA) scheme, with IKONOS panchromatic imagery having 1 meter resolution. For this, the GDPA scheme and its main modules were reviewed with processing steps and implemented as a prototype software. Using the extracted bi-level image and ground truth coming from actual GIS layer, overall accuracy evaluation and ranking error-assessment were performed. As the processed results, road information can be automatically extracted; by the way, it is pointed out that some user-defined variables should be carefully determined in using high-resolution satellite imagery in the dense or low contrast areas. While, the GDPA method needs additional processing, because direct results using this method do not produce high overall accuracy or ranking value. The main advantage of the GDPA scheme on road features extraction can be noted as its performance and further applicability. This experiment study can be extended into practical application fields related to remote sensing.

• Journal of the Optical Society of Korea
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• 제17권6호
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• pp.500-505
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• 2013

In this paper, we propose a novel framework to evaluate the depth resolution of axially distributed stereo sensing (ADSS) under fixed resource constraints. The proposed framework can evaluate the performance of ADSS systems based on various sensing parameters such as the number of cameras, the number of total pixels, pixel size and so on. The Monte Carlo simulations for the proposed framework are performed and the evaluation results are presented.