• 대한원격탐사학회지
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• 제35권6_4호
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• pp.1391-1401
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• 2019

KOMPSAT-3A는 2015년 한국항공우주연구원(KARI)이 발사한 고해상 광학위성으로 0.55 m 급 전정색영상(PAN), 2.2 m 급 다중 분광 영상(MS) 그리고 5.5 m 급 중적외선 영상(MIR_OR)을 제공한다. 그러나 보안 또는 군사적인 문제로 인해 공간 해상도 5.5 m MIR_OR 영상은 33 m 공간해상도로 down-sampling된 MIR_rd 영상으로 제공된다. 본 연구에서는 가상의 고주파(HP) 영상과 최적 융합 계수를 이용하여 MIR_rd 영상의 공간해상도를 복원하는 방법을 제안하였다. MS 영상과 MIR_rd 영상을 이용하여 가상의 MIR_OR^fus 영상을 제작하였으며, 이를 실제 MIR_OR 영상과 비교 분석하였다. 실험 결과, 제안된 방법이 MS 영상의 공간해상도와 MIR_rd 영상의 분광정보를 효과적으로 조합 하였다는 것을 보여주었다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.109-113
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• 2007

The COMS provides the LRIT/HRIT services to users. The COMS LRIT/HRIT broadcast service should satisfy the 15 minutes timeliness requirement. The requirement is important and critical enough to impact overall performance of the LHGS. HRIT image data is acquired from INRSM output receiving but LRIT image data is generated by sub-sampling HRIT image data in the LHGS. Specially, since LRIT is acquired from sub-sampled HRIT image data, LRIT processing spent more time. Besides, some of data loss for LRIT occurs since LRIT is compressed by lossy JPEG. Therefore, algorithm with the fastest processing speed and simplicity to be implemented should be selected to satisfy the requirement. Investigated sub-sampling algorithm for the LHGS were nearest neighbour algorithm, bilinear algorithm and bicubic algorithm. Nearest neighbour algorithm is selected for COMS LHGS considering the speed, simplicity and anti-aliasing corresponding to the guideline of user (KMA: Korea Meteorological Administration) to maintain the most cloud itself information in a view of meteorology. But the nearest neighbour algorithm is known as the worst performance. Therefore, it is studied in this paper that the selection of nearest neighbour algorithm for the LHGS is reasonable. First of all, characteristic of 3 sub-sampling algorithms is studied and compared. Then, several sub-sampling algorithm were applied to MTSAT-1R image data corresponding to COMS HRIT. Also, resized image was acquired from sub-sampled image with the identical sub-sampling algorithms applied to sub-sampling from HRIT to LRIT. And the difference between original image and resized image is compared. Besides, PSNR and MSE are calculated for each algorithm. This paper shows that it is appropriate to select nearest neighbour algorithm for COMS LHGS since sub-sampled image by nearest neighbour algorithm is little difference with that of other algorithms in quality performance from PSNR.

• Journal of the Optical Society of Korea
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• 제18권4호
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• pp.388-394
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• 2014

In this paper, we propose a three-dimensional (3D) image correlator by use of computational integral imaging reconstruction based on the modified convolution property of periodic functions (CPPF) for recognition of partially occluded objects. In the proposed correlator, elemental images of the reference and target objects are picked up by a lenslet array, and subsequently are transformed to a sub-image array which contains different perspectives according to the viewing direction. The modified version of the CPPF is applied to the sub-images. This enables us to produce the plane sub-image arrays without the magnification and superimposition processes used in the conventional methods. With the modified CPPF and the sub-image arrays, we reconstruct the reference and target plane sub-image arrays according to the reconstruction plane. 3D object recognition is performed through cross-correlations between the reference and the target plane sub-image arrays. To show the feasibility of the proposed method, some preliminary experiments on the target objects are carried out and the results are presented. Experimental results reveal that the use of plane sub-image arrays enables us to improve the correlation performance, compared to the conventional method using the computational integral imaging reconstruction algorithm.

• Journal of applied mathematics & informatics
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• 제41권5호
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• pp.1115-1128
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• 2023

In this paper, a novel hybrid method for multi-focus image fusion is proposed. The method combines the advantages of wavelet transform-based methods and focus-measure-based methods to achieve an improved fusion result. The input images are first decomposed into different frequency sub-bands using the discrete wavelet transform (DWT). The focus measure of each sub-band is then calculated using the Laplacian of Gaussian (LoG) operator, and the sub-band with the highest focus measure is selected as the focused sub-band. The focused sub-band is sharpened using an unsharp masking filter to preserve the details in the focused part of the image.Finally, the sharpened focused sub-bands from all input images are fused using the maximum intensity fusion method to preserve the important information from all focus images. The proposed method has been evaluated using standard multi focus image fusion datasets and has shown promising results compared to existing methods.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2015년도 추계학술대회
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• pp.180-181
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• 2015

In this paper, we present a consistent and efficient edit propagation method that is applied for light field data. Unlike conventional sparse edit propagation, the coherency between light field sub-aperture images is fully considered by utilizing light field consistency in the optimization framework. Instead of directly solving the optimization function on all light field sub-aperture images, the proposed optimization framework performs sparse edit propagation in the extended focus image domain. The extended focus image is the representative image that contains implicit depth information and the well-focused region of all sub-aperture images. The edit results in the extended focus image are then propagated back to each light field sub-aperture image. Experimental results on test images captured by a Lytro off-the-shelf light field camera confirm that the proposed method provides robust and consistent results of edited light field sub-aperture images.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권9호
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• pp.2882-2903
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• 2022

Image super-resolution (SR) processing is of great value in the fields of digital image processing, intelligent security, film and television production and so on. This paper proposed a densely connected deep learning network based on cascade architecture, which can be used to solve the problem of super-resolution in the field of image quality enhancement. We proposed a more efficient residual scaling dense block (RSDB) and the multi-channel cascade architecture to realize more efficient feature reuse. Also we proposed a hybrid loss function based on L₁ error and L_∞ error to achieve better L_∞ error performance. The experimental results show that the overall performance of the network is effectively improved on cascade architecture and residual scaling. Compared with the residual dense net (RDN), the PSNR / SSIM of the new method is improved by 2.24% / 1.44% respectively, and the L_∞ performance is improved by 3.64%. It shows that the cascade connection and residual scaling method can effectively realize feature reuse, improving the residual convergence speed and learning efficiency of our network. The L_∞ performance is improved by 11.09% with only a minimal loses of 1.14% / 0.60% on PSNR / SSIM performance after adopting the new loss function. That is to say, the L_∞ performance can be improved greatly on the new loss function with a minor loss of PSNR / SSIM performance, which is of great value in L_∞ error sensitive tasks.

• Korean Journal of Radiology
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• 제22권8호
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• pp.1341-1351
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• 2021

Objective: To compare the quality of various polychromatic and monochromatic images with or without using an iterative metal artifact reduction algorithm (iMAR) obtained from a dual-energy computed tomography (CT) to evaluate total knee arthroplasty. Materials and Methods: We included 58 patients (28 male and 30 female; mean age [range], 71.4 [61-83] years) who underwent 74 knee examinations after total knee arthroplasty using dual-energy CT. CT image sets consisted of polychromatic image sets that linearly blended 80 kVp and tin-filtered 140 kVp using weighting factors of 0.4, 0, and -0.3, and monochromatic images at 130, 150, 170, and 190 keV. These image sets were obtained with and without applying iMAR, creating a total of 14 image sets. Two readers qualitatively ranked the image quality (1 [lowest quality] through 14 [highest quality]). Volumes of high- and low-density artifacts and contrast-to-noise ratios (CNRs) between the bone and fat tissue were quantitatively measured in a subset of 25 knees unaffected by metal artifacts. Results: iMAR-applied, polychromatic images using weighting factors of -0.3 and 0.0 (P_-0.3i and P_0.0i, respectively) showed the highest image-quality rank scores (median of 14 for both by one reader and 13 and 14, respectively, by the other reader; p < 0.001). All iMAR-applied image series showed higher rank scores than the iMAR-unapplied ones. The smallest volumes of low-density artifacts were found in P_-0.3i, P_0.0i, and iMAR-applied monochromatic images at 130 keV. The smallest volumes of high-density artifacts were noted in P_-0.3i. The CNRs were best in polychromatic images using a weighting factor of 0.4 with or without iMAR application, followed by polychromatic images using a weighting factor of 0.0 with or without iMAR application. Conclusion: Polychromatic images combined with iMAR application, P_-0.3i and P_0.0i, provided better image qualities and substantial metal artifact reduction compared with other image sets.

• 한국산학기술학회논문지
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• 제13권3호
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• pp.1330-1336
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• 2012

영상 검색 방법은 텍스트 기반, 내용 기반, 영역 기반 영상 검색, 부분 영상 검색 방법 등 다양한 연구가 이루어지고 있다. 그 중에 부분 영상 검색은 질의 영상을 포함하는 대상 영상을 찾는 문제이다. 본 논문에서는 생물정보학에서 사용하는 점 행렬 방법을 이용한 새로운 부분 영상 검색 방법을 제안한다. 점 행렬은 두 DNA 서열 간에 유사도를 시각화하는 방법으로써 영상 검색에 적용하여 두 영상 간에 유사도를 비교하는 문제로 재정의한다. 이 알고리즘을 적용하기 위해서 이차원 배열 정보인 영상을 일차원 명암도 영상으로 변환한다. 두 일차원 명암도 영상을 정렬하여 생성된 점 행렬을 이용하여 부분 영상 후보 영역을 생성한다. 실험에는 10 개의 대상 영상과 대상 영상의 부분을 복사한 영상, 축소한 영상, 확대한 영상으로 5종류의 질의 영상을 사용하였다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 신호처리소사이어티 추계학술대회 논문집
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• pp.359-362
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• 2003

In PDP(Plasma Display Panel), sub-field method is used to implement gray scale. Each sub-field has different periods. And Every gray level has information of which sub-field has to be displayed. This is called sub-field mapping. There are several sub-field mapping values in some gray levels. So, it is possible to select best choice in this paper, we propose new sub field mapping method using a fuzzy inference system to select best sub-field mapping values in accordance with input image and environment temperature. In order to implement fuzzy system, we used MATLAB fuzzy inference editor.

• Journal of Information Processing Systems
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• 제17권6호
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• pp.1170-1178
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• 2021

This paper proposed a versatile algorithm based on a dual-tree complex wavelet transform for intensifying the visual aspect of medical images. First, the decomposition of the input image into a high sub-band and low-sub-band image is done. Further, to improve the resolution of the resulting image, the high sub-band image is interpolated using Lanczos interpolation. Also, contrast enhancement is performed by singular value decomposition (SVD). Finally, the image reconstruction is achieved by using an inverse wavelet transform. Then, the Gaussian filter will improve the visual quality of the image. We have collected images from the hospital and the internet for quantitative and qualitative analysis. These images act as a reference image for comparing the effectiveness of the proposed algorithm with the existing state-of-the-art. We have divided the proposed algorithm into several stages: preprocessing, contrast enhancement, resolution enhancement, and visual quality enhancement. Both analyses show the proposed algorithm's effectiveness compared to existing methods.