• Spatial Information Research
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• 제13권4호
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• pp.345-354
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• 2005

초해상도 영상복원은 동일 지역을 촬영한 여러 장의 저해상도 영상을 이용하여 고해상도의 영상으로 재구성하는 영상처리 알고리즘 기법이다. 이 기법은 위성영상, 비디오 감시, 영상 강조 및 복원, 영상 모자이킹, 의료 영상과 같이 여러 장의 프레임 영상을 획득할 수 있는 분야에서 유용하게 사용될 수 있다. 본 연구에서는 지상을 촬영한 비디오 영상 열에 공간영역 초해상도 기법을 적용하였다. 실험에 사용된 영상은 높은 중복도로 촬영된 연속적인 비디오 영상에서 부표본화되었으며, 저해상도 영상과 고해상도 영상간의 관측 모델을 구성하고 초해상도 영상복원 기법중의 하나인 MAP 알고리즘을 적용하였다. MAP 기법을 이용하여 여러 장의 저해상도 영상에서 고해상도 영상으로 복원하였으며, 그 결과를 기존의 영상보간 방법들과 비교하였다.

• 대한전자공학회논문지SD
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• 제46권5호
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• pp.39-48
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• 2009

1984년 처음 SR 알고리즘이 제안된 이후, 많은 SR 복원 알고리즘이 제안되었다 SR의 접근방법 중에서도 공간적 접근방법은 저해상도 이미지의 픽셀 값을 고해상도 이미지 격자에 매핑 함으로써 이루어진다. 이때, 저해상도 이미지들 간의 각각 다른 노이즈와 다른 PSF(Point Spread Function) 함수, 왜곡으로 인해 매핑 시 문제가 된다. 때문에 저해상도 이미지들의 노이즈 성분을 최소화하는 방법이 필요하다. 본 논문에서는 노이즈 성분을 최소화하는 방법으로 L1 norm의 방법을 사용하고 이와 동시에 이미지의 경계를 보완해주는 Huber norm을 사용하는 SR의 구조를 제안한다. 실험에서는 타 알고리즘과의 비교를 통해 제안한 알고리즘이 저해상도 이미지 상에 존재하는 노이즈를 줄이고 이미지 경계부분의 보완을 확인하였다.

• Spatial Information Research
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• 제19권1호
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• pp.29-40
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• 2011

정지궤도 해색 센서(GOCI: Geostationary Ocean Color Imager) 는 세계 최초의 정지궤도 위성으로 매일 1 시간마다 8 장의 영상을 획득 할 수 있어 육상파 해양 모두 활용성이 높은 위성이다. 그러나 500m의 GSD(Ground Sample Distance)를 지니는 서해성도 영상은 육성 활용에 한계가 있다. 최근, 컴퓨터 비전분야에서 활발히 진행 중인 기술인 Super Resolution(이하 SR)는 유사 시간대에 촬영한 저해상도 영상으로부터 고해상도 영상을 제작하는 기술로, 이를 시간 해상도가 높은 시계열 위성인 GOCI에 적용한다면 해상도가 향상 된 영상을 제작하는 기술로, 이를 시간 해상도가 높은 시계열 위성인 GOCI에 적용한다면 해상도가 향상 된 영상의 취득이 가능하며, 또한 광학 위성 영상의 단점인 구름에 의해 손실된 지상 정보의 복원이 가능할 것이다. 본 연구에서는, GOCI 자료를 위한 효율적인 초해상도 영상 복원 알고리즘 개발을 위한 선행연구로써 위성 영상 취득과정과 유사한 환경의 시뮬레이션을 통해 시계열 자료를 제작하고, 제작된 자료를 제안한 알고리즘에 적용함으로서 0.1 단위의 픽셀 정합도를 확인하였고, 원본 영상과 RMSE 0.5763, PSNR 52.9183 db, SSIM Index 0.9486의 정확도를 나타낸 HR 영상을 복원하였다.

• Journal of Information Processing Systems
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• 제18권4호
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• pp.575-586
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• 2022

Uneven light in real-world causes visual degradation for underexposed regions. For these regions, insufficient consideration during enhancement procedure will result in over-/under-exposure, loss of details and color distortion. Confronting such challenges, an unsupervised low-light image enhancement network is proposed in this paper based on the guidance of the unpaired low-/normal-light images. The key components in our network include super-resolution module (SRM), a GAN-based low-light image enhancement network (LLIEN), and denoising-scaling module (DSM). The SRM improves the resolution of the low-light input images before illumination enhancement. Such design philosophy improves the effectiveness of texture details preservation by operating in high-resolution space. Subsequently, local lightness attention module in LLIEN effectively distinguishes unevenly illuminated areas and puts emphasis on low-light areas, ensuring the spatial consistency of illumination for locally underexposed images. Then, multiple discriminators, i.e., global discriminator, local region discriminator, and color discriminator performs assessment from different perspectives to avoid over-/under-exposure and color distortion, which guides the network to generate images that in line with human aesthetic perception. Finally, the DSM performs noise removal and obtains high-quality enhanced images. Both qualitative and quantitative experiments demonstrate that our approach achieves favorable results, which indicates its superior capacity on illumination and texture details restoration.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 Proceedings of the Korea Automatic Control Conference, 11th (KACC); Pohang, Korea; 24-26 Oct. 1996
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• pp.409-412
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• 1996

Ultrasonic sensors are widely used in various applications due to advantages of low cost, simplicity in construction, mechanical robustness, and little environmental restriction in usage. But the main purposes of the noncontact sensing are rather narrowly confined within object detection and distance measurement. For the application of object recognition, ultrasonic sensors exhibit several shortcomings of poor directionality which results in low spatial resolution of objects, and specularity which gives frequent erroneous range readings. To resolve these problems in object recognition, an array of the sensor has been used. To improve the spatial resolution, more number of sensors are used in essence throughout the various devices of the sensor arrays. Under the disguise of a fixed number of the sensors, the array can be shifted mechanically in several steps. In this paper we propose a practical sensor resolution enhancement method using an electronic circuit accompanying the sensor array. The circuit changes the transmitter output voltage in several steps. Using the known sensor characteristics, a set of different return echo signals provide enhanced spatial resolution. The improvement is obtained with neither the cost of the increased number of the sensors nor extra mechanical devices.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1999년도 하계종합학술대회 논문집
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• pp.687-690
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• 1999

Many high-resolution algorithms based on the eigen-decomposition analysis of observed covariance matrix, such as MVE, MUSIC, and EVM, have been proposed. However, the resolution of spectral estimates for these algorithms is severely degraded when Signal-to-Noise Ratio (SNR) is low and arrival angles of signal are close to each other. And EVM and MUSIC is powerful for the characteristic of SNR. But have the limitation that the number of signals presented is known. While MVE is bad the characteristic of SNR. In this study, we propose a modified MVE to enhance the resolution for Direction-Of-Arrival (DOA) estimation of underwater acoustic signal. This is to remove the limitation that existing algorithms should know the information for the number of signals. Because the algorithms founded on the eigen value estimate DOA with only the noise subspace, they have the high-resolution characteristic. And then, with the method reducing the effect of the signal subspace, we are to reduce the degradation because of complementary relationship between the signal subspace and the noise subspace. This paper, with using the simulation data, we have estimated the proposed algorithms, compared it with other high-resolution algorithms. The simulation results show that the modified MVE proposed is accurate and has a better resolution even though SNR is low, under the same condition.

• 한국멀티미디어학회논문지
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• 제17권12호
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• pp.1393-1401
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• 2014

This paper presents an adaptive image interpolation method using a pixel-based neighbor embedding which is modified from the patch-based neighbor embedding of contemporary super resolution algorithms. Conventional interpolation methods for high resolution detect at least 16-directional edges in order to remove zig-zaging effects and selectively choose the interpolation strategy according to the direction and value of edge. Thus, they require much computation and high complexity. In order to develop a simple interpolation method preserving edge's directional shape, the proposed algorithm adopts the simplest Haar wavelet and suggests a new pixel-based embedding scheme. First, the low-quality image but high resolution, magnified into 1 octave above, is acquired using an adaptive 8-directional interpolation based on the high frequency coefficients of the wavelet transform. Thereafter, the pixel embedding process updates a high resolution pixel of the magnified image with the weighted sum of the best matched pixel value, which is searched at its low resolution image. As the results, the proposed scheme is simple and removes zig-zaging effects without any additional process.

• 한국CDE학회논문집
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• 제11권4호
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• pp.315-325
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• 2006

It is very often necessary to search for similar parts during designing a new product because its parts are often easily designed by modifying existing similar parts. In this way, the design time and cost can be reduced. Thus it would be nice to have an efficient similarity comparison algorithm that can be used anytime in the design process. There have been many approaches to compare shape similarity between two solids. In this paper, two parts represented in B-Rep is compared in two steps: one for overall appearances and the other for detail features. In the first step, geometric information is used in low level of detail for easy and fast pre-classification by the overall appearance. In the second step, feature information is used to compare the detail shape in high level of detail to find more similar design. To realize the idea above, a multi resolution algorithm is proposed so that a given solid is described by an overall appearance in a low resolution and by detail features in high resolution. Using this multi-resolution representation, parts can be compared based on the overall appearance first so that the number of parts to be compared in high resolution is reduced, and then detail features are investigated to retrieve the most similar part. In this way, computational time can be reduced by the fast classification in the first step while reliability can be preserved by detail comparison in the second step.

• Nuclear Engineering and Technology
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• 제53권7호
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• pp.2277-2288
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• 2021

To regulate the safety protocols in nuclear facilities, radioactive aerosols have been extensively researched to understand their health impacts. However, most measured particle-size distributions remain at low resolutions, with the particle sizes ranging from nanometer to micrometer. This study combines the high-resolution detection of 500 size classes, ranging from 6 nm to 10 ㎛, for aerodynamic diameter distributions, with a regional lung deposition calculation. We applied the new approach to characterize particle-size distributions of aerosols generated during the plasma arc cutting of simulated non-radioactive steel alloy wastes. The high-resolution measured data were used to calculate the deposition ratios of the aerosols in different lung regions. The deposition ratios in the alveolar sacs contained the dominant particle sizes ranging from 0.01 to 0.1 ㎛. We determined the distribution of various metals using different vapor pressures of the alloying components and analyzed the uncertainties of lung deposition calculations using the low-resolution aerodynamic diameter data simultaneously. In high-resolution data, the changes in aerosols that can penetrate the blood system were better captured, correcting their potential risks by a maximum of 42%. The combined calculations can aid the enhancement of high-resolution measuring equipment to effectively manage radiation safety in nuclear facilities.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2003년도 추계학술발표회 논문집
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• pp.379-384
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• 2003

In this paper, we introduce a change detection system that can extract and analyze change elements from high-resolution satellite imagery as well as low- or middle-resolution satellite imagery. The developed system provides not only 7 pixel-based methods that can be used to detect change from low- or middle-resolution satellite images but also a float window concept that can be used in manual change detection from high-resolution satellite images. This system enables fast process of the very large image, because it is constituted by OGC grid coverage components. Also new change detection algorithms can be easily added into this system if once they are made into grid coverage components.