• 대한원격탐사학회지
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• 제28권4호
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• pp.347-355
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• 2012

본 연구에서는 MNF 변환 후 각 밴드별 최소, 최대값을 가지는 화소들을 추출하고, 이 후보 화소들만을 대상으로 endmemeber를 추출하는 기법을 제안하고 이의 적용 가능성을 고찰하였다. 이와 같은 접근은 영상자료의 크기와 관계없이 밴드수${\times}$2개에 해당하는 화소들만을 대상으로 endmember를 추출하므로 전체 화소를 대상으로 endmember 여부를 계산하는 기존의 기법들보다 계산시간 측면에서 매우 효율적일 수 있다. 모의 초분광 영상자료 및 미국 네바다 Cuprite 지역의 AVIRIS 초분광 영상자료에 N-FINDR 기법을 적용하여 endmember를 추출함에 있어 본 기법을 적용해본 결과, 전체 화소를 대상으로 처리한 결과와 거의 동일한 결과를 얻을 수 있음을 확인하였다. 잡음에 의한 영항과 후보 화소 추출기준 등에 대한 추가 연구를 통해 대용량 초분광 영상자료의 처리 및 분석에 효율적으로 활용될 수 있을 것으로 기대된다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권3호
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• pp.1785-1801
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• 2017

In recent years, image encryption algorithms have been developed rapidly in order to ensure the security of image transmission. With the assistance of our previous work, this paper proposes a novel chaotic image encryption algorithm based on self-adaptive model and feedback mechanism to enhance the security and improve the efficiency. Different from other existing methods where the permutation is performed by the self-adaptive model, the initial values of iteration are generated in a novel way to make the distribution of initial values more uniform. Unlike the other schemes which is on the strength of the feedback mechanism in the stage of diffusion, the piecewise linear chaotic map is first introduced to produce the intermediate values for the sake of resisting the differential attack. The security and efficiency analysis has been performed. We measure our scheme through comprehensive simulations, considering key sensitivity, key space, encryption speed, and resistance to common attacks, especially differential attack.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권8호
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• pp.1843-1859
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• 2013

The continuous increase of the spatial resolution of remote sensing images brings great challenge to image analysis and processing. Traditional prior knowledge-based region detection and target recognition algorithms for processing high resolution remote sensing images generally employ a global searching solution, which results in prohibitive computational complexity. In this paper, a more efficient region of interest (ROI) detection algorithm based on visual attention and threshold segmentation (VA-TS) is proposed, wherein a visual attention mechanism is used to eliminate image segmentation and feature detection to the entire image. The input image is subsampled to decrease the amount of data and the discrete moment transform (DMT) feature is extracted to provide a finer description of the edges. The feature maps are combined with weights according to the amount of the "strong points" and the "salient points". A threshold segmentation strategy is employed to obtain more accurate region of interest shape information with the very low computational complexity. Experimental statistics have shown that the proposed algorithm is computational efficient and provide more visually accurate detection results. The calculation time is only about 0.7% of the traditional Itti's model.

• Journal of Magnetics
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• 제18권3호
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• pp.311-316
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• 2013

Digital image processing has increasingly been implemented in nanostructural analysis and would be an ideal tool to characterize the morphology and position of self-assembled magnetic nanoparticles for high density recording. In this work, magnetic nanoparticles were synthesized by the modified polyol process using $Fe(acac)_3$ and $Pt(acac)_2$ as starting materials. Transmission electron microscope (TEM) images of as-synthesized products were inspected using an image processing procedure. Grayscale images ($800{\times}800$ pixels, 72 dot per inch) were converted to binary images by using Otsu's thresholding. Each particle was then detected by using the closing algorithm with disk structuring elements of 2 pixels, the Canny edge detection, and edge linking algorithm. Their centroid, diameter and area were subsequently evaluated. The degree of polydispersity of magnetic nanoparticles can then be compared using the size distribution from this image processing procedure.

• 한국인공지능학회지
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• 제12권1호
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• pp.1-6
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• 2024

Recently, various techniques are being applied through the development of medical AI, and research has been conducted on the application of super-resolution AI models. In this study, evaluate the results of the application of the super-resolution AI model to brain CT as the basic data for future research. Acquiring CT images of the brain, algorithm for brain and bone windowing setting, and the resolution was downscaled to 5 types resolution image based on the original resolution image, and then upscaled to resolution to create an LR image and used for network input with the original imaging. The SRCNN model was applied to each of these images and analyzed using PSNR, SSIM, Loss. As a result of quantitative index analysis, the results were the best at 256×256, the brain and bone window setting PSNR were the same at 33.72, 35.2, and SSIM at 0.98 respectively, and the loss was 0.0004 and 0.0003, respectively, showing relatively excellent performance in the bone window setting CT image. The possibility of future studies aimed image quality and exposure dose is confirmed, and additional studies that need to be verified are also presented, which can be used as basic data for the above studies.

• 자원환경지질
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• 제32권1호
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• pp.19-31
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• 1999

In this study, we have estimated lineaments in the Euiseong area, Kyungbuk Province, from Landsat TM by applying the algorithm developed by Kim and Won et al. which can effectively reduce the look direction bias associated with the Sun's azimuth angle. Fratures over the study area were also mapped in the field at 57 selected sites to compare them with the results from the satellite image. The trends of lineaments estimated from the Landsat TM images are characterized as $N50^{\circ}$~70W, NS~$N10^{\circ}$W, and $N10^{\circ}$~$60^{\circ}$E trends. The spatial distribution of lineaments is also studied using a circular grid, and the results show that the area can be divided into two domains : domain A in which NS~$N20^{\circ}$E direction is dominant, and domain B in which west-north-west direction is prominent. The trends of lineaments can also be classified into seven groups. Among them, only C, D and G trends are found to be dominant based upon Donnelly's nearest neighbor analysis and correlations of lineament desities. In the color composite image produced by overlaying the lineament density map of these C-, D-, and G-trends, G-trend is shown to be developed in the whole study area while the eastern part of the area is dominated by D-trend. C-trend develops extensively over the whole are except the southeastern part. The orientation of fractures measured at 35 points in the field shows major trends of NS~$N30^{\circ}$E, $N50^{\circ}$~$80^{\circ}$W, and N80$^{\circ}$E~EW, which agree relatively well with the lineaments estimated form the satellite image. The rose diagram analysis fo field data shows that WNW-ESE trending discontinuities are developed in the whole area while discontinuities of NS~$N20^{\circ}$E are develped only in the estern part, which also coincide with the result from the satellite image. The combined results of lineaments from the satellite image and fracture orientation of field data at 22 points including 18 minor faults in Sindong Group imply that the WNW-ESE trend is so prominent that Gumchun and Gaum faults are possibly extended up to the lower Sindong Group in the study area.

• Journal of Astronomy and Space Sciences
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• 제8권1호
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• pp.115-123
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• 1991

Automatching algorithm is suitable for cross-correlation, which showed correlation surface about maximal correlation coefficient. The size of the window area must be determined empirically, whereas window size generally chosen as a compromise between speed and accuracy. It is possible that epipolar transform prevented from mismatching and decreased search space. In application of the astronomical fields, automatching algorithm mainly used to planet surface recovery in satellite image.

• 한국멀티미디어학회논문지
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• 제18권6호
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• pp.701-709
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• 2015

Image stitching method is a technique for obtaining an high-resolution image by combining two or more images. In X-ray image for clinical diagnosis, the size of the imaging region taken by one shot is limited due to the field-of-view of the equipment. Therefore, in order to obtain a high-resolution image including large regions such as a whole body, the synthesis of multiple X-ray images is required. In this paper, we propose a rapid stitching method of digital X-ray images using template-based registration. The proposed algorithm use principal component analysis(PCA) and k-nearest neighborhood(k-NN) to determine the location of input images before performing a template-based matching. After detecting the overlapping position using template-based matching, we synthesize input images by alpha blending. To improve the computational efficiency, reduced images are used for PCA and k-NN analysis. Experimental results showed that our method was more accurate comparing with the previous method with the improvement of the registration speed. Our stitching method could be usefully applied into the stitching of 2D or 3D multiple images.

• 한국정보통신학회논문지
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• 제8권3호
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• pp.721-726
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• 2004

영상의 이진화는 문자 인식, 영상 분석 등 다양한 영상 처리 분야의 전처리 과정으로 자주 적용되고 있다. 영상 이진화는 임계치의 설정에 따라 처리 성능이 좌우되며, 대부분의 기존 이진화 방법은 밝기 값의 히스토그램을 사용하여 평균 밝기 값이나 히스토그램의 골짜기를 임계치로 설정한다. 이와 같은 방법은 양봉의 특징을 보이지 않거나 특정 영상을 추출하려는 경우에는 적절한 임계치를 얻기 어렵다. 따라서 본 논문에서는 그레이 스케일 영상에서 밝기 값을 여러 구간으로 분할하여 각 구간의 밝기 평균값을 구하고, 두 개의 구간에 대해 평균값 사이의 거리를 각 구간에서 평균값과 양극과의 거리 비율로 나누어서 계산된 값을 두 개의 구간을 합친 새로운 구간의 임계치로 설정한다. 최종적으로 하나의 구간이 생성될 때까지 구간 통합과 임계값 계산을 반복함으로써 이진화 임계값을 산출한다. 제안된 이진화 방법의 성능을 평가하기 위하여 다양한 종류의 영상에 적용한 결과, 기존의 이진화 방법들보다 효율적인 것을 확인하였다.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2002년도 추계학술발표회 논문집
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• pp.205-208
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• 2002