• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.4
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• pp.127-136
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• 2013

This paper proposes a video deblurring algorithm which maintains uniform sharpness between frames. Unlike the previous algorithms using fixed parameters, the proposed algorithm keeps uniform sharpness by adjusting parameters for each frame. First, we estimate the initial blur kernel and perform deconvolution, then measure the sharpness of the deblurred image. In order to maintain uniform sharpness, we adjust the regularization parameter and kernel according to the examined sharpness, and perform deconvolution again. The experimental results show that the proposed algorithm achieves outstanding deblurring results while providing consistent sharpness.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.1
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• pp.49-56
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• 2020

In this study, we analyzed the sharpness of UAV-images using the gradient formula and produced a MATLAB GUI (Graphical User Interface)-based sharpness analysis tool for easy use. In order to verify the reliability of the proposed sharpness analysis method, sharpness values of the UAV-images measured by the proposed method were compared with those by measured the commercial software Metashape of the Agisoft. As a result of measuring the sharpness with both tools on 10 UAV-images, sharpness values themselves were different from each other for the same image. However, there was constant bias of 011 ~ 0.20 between two results, and then the same sharpness was obtained by eliminating this bias. This fact proved the reliability of the proposed sharpness analysis method in this study. In addition, in order to verify the practicality of the proposed sharpness analysis method, unsharp images were classified as low quality ones, and the quality of orthoimages was compared each other, which were generated included low quality images and excluded them. As a result, the quality of orthoimage including low quality images could not be analyzed due to blurring of the resolution target. However, the GSD (Ground Sample Distance) of orthoimage excluding low quality images was 3.2cm with a Bar target and 4.0cm with a Siemens star thanks to the clear resolution targets. It therefore demonstrates the practicality of the proposed sharpness analysis method in this study.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.12a
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• pp.109-112
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• 2000

고역의 주파수 성분이 감쇠되어 선명도가 저하된 이미지나 선형 보간법에 의해 확대된 이미지의 계단모양 왜곡을 감소시킴으로써 경계선의 선명도가 저하된 이미지들을 위해 형태학적 처리(morphological processing)에 의한 이미지 윤곽선의 선명도를 향상시키는 방법을 제안하였다. 본 논문에서는 블러링(blurring)된 이미지를 화소의 명암에 따라 다수개의 평판 이미지(slice image)로 나누고 각 평판 이미지에 대해 반복적인 최대/최소값 필터(min/max filter)의 적용으로 얻어진 윤곽선의 중심을 기준으로 하여 팽창(dilation)과 침식(erosion)을 수행함으로 이미지의 윤곽선에서의 명암 변화에 대한 경사도를 크게 만들고 이로써 이미지 윤곽선의 선명도를 향상시키는 방법을 사용하였으며 모의 시험결과를 통하여 고역 주파수 강조에 의한 방법에 비하여 인위적인 잡음(artifact)없이 효과적으로 선명도를 향상시킬 수 있음을 보였다.

• Journal of Broadcast Engineering
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• v.16 no.3
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• pp.552-560
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• 2011

In this paper, a new no-reference sharpness measure using frequency domain coefficients is proposed. Although most existing sharpness measures used pixel intensity to compute the blur degree, the proposed sharpness measure computes the sharpness using frequency coefficients. To assess the perceived sharpness of a given image, the image is re-blurred by a Gaussian low pass filter and a new quality measure function was defined using the frequency domain coefficients of the given image and the re-blurred image. To evaluate the proposed algorithms, TID2008 quality assessment database was used. Experimental results show that the proposed quality assessment method showed high correlation with the subjective scores.

• Proceedings of the Acoustical Society of Korea Conference
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• autumn
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• pp.257-260
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• 2004

HRTF 를 사용하여 가상적인 음향 효과를 내는 시스템에서의 음의 왜곡은 필수적이다. 하지만 음성과 같은 사람이 민감하게 느끼는 부분에서의 음의 선명도 저하는 다른 대역의 왜곡보다 더욱 크게 느껴진다. 그리고 모노 및 두 채널의 주파수 특성이 비슷한 스테레오에서는 음질을 보상할 수 없다는 단점이 있다. 본 논문에서는 이러한 음의 선명도의 저하를 유발하게 하는 가상 음향 발생 필터의 특징을 분석하고, 간단한 필터 설계에 의해서 본래의 가상 음향을 그대로 유지하면서 선명도를 높일 수 있는 방법을 제시한다. 제시한 방법은 특히 모노 및 뉴스모드와 같이 음성이 많이 들어 있는 부분에서 뛰어난 성능을 보인다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.06a
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• pp.189-190
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• 2016

일반 영상의 영상확대를 위한 다양한 알고리즘이 존재한다. 하지만 적외선 열화상 영상의 경우 일반영상과 다른 특성을 가지고 있기 때문에 적외선 영상을 위한 영상 확대 알고리즘이 필요하다. 따라서 적외선 영상이 일반영상에 비해 디테일이 없다는 특성을 고려하여 복잡한 알고리즘을 적용시키기 보다는 ADRC 와 같은 단순한 분류 기법을 활용하여 LR-HR 패치를 분류하고 학습된 데이터를 이용하여 영상확대 알고리즘에 적용하였다. 알고리즘의 성능 향상을 위해 학습과정에 전처리 과정을 추가하여 합성과정에서 추가적인 연산량의 증가 없이 확대 영상의 선명도를 향상시키고자 하였다. 또한 확대된 적외선 영상이 동일 해상도의 가시광영상에 비해 선명도가 떨어진다는 점을 고려하여 확대된 적외선 영상에 가시광영상의 고주파 정보를 합성시켜 이전보다 영상의 선명도를 더 향상시키고자 하였다. 이와 같은 방법으로 영상 확대 알고리즘만 수행하였을 때 통상적인 영상확대 기법인 bi-cubic interpolation 기법보다 JNB 수치가 평균 0.0727 만큼 높은 결과를 확인할 수 있었고 가시광영상과 융합하였을 때 이전보다 평균 0.0742 만큼 더 선명해진 영상을 얻었다.

• Proceedings of the Korea Multimedia Society Conference
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• 1998.10a
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• pp.232-236
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• 1998

이미지가 전경과 배경으로 이루어져 있을 경우, 이미지에서 중요한 대부분의 정보는 전경의 영역에 집중하게 된다. 만약 이미지를 전경과 배경으로 구분할 수 있다면 영상 인식, 영상 합성, 영상 압축 등 여러 분야에 유용하게 활용할 수 있게 된다. 본 논문에서는 선명도 차이를 이용하여 이미지를 전경과 배경으로 분할하는 방법을 소개하고, 그 실험 결과를 보인다.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.11
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• pp.56-63
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• 2012

In this paper, adaptive unsharp masking using bilateral filter, edge-preserving smoothing filter is proposed to reduce the overshoot and jagging artifact in sharpening images. Previous image enhancement methods including unsharp masking(UM) can emphasize high-frequency details strongly, but often cause several artifacts such as overshooting, noise, jagging and so on. Proposed image enhancement method preserves edges well because of using bilateral filter and sensitively controls a weight according to edge's directions. Therefore, it enhances sharpness and effectively reduces overshoot and jagging artifacts. Simulation results comparing output of previous AUM with proposed method show that proposed algorithm makes images properly enhanced, and we know that overshoot and jagging artifacts are many reduced.

• Journal of Broadcast Engineering
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• v.15 no.3
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• pp.368-379
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• 2010

As high-definition video is broadly used in various system such as broadcast system and digital camcorder the proper method in order to improve the quality of high-definition video is needed. In this paper, we propose an efficient method to improve color and contrast of high-definition video. In order to apply the image enhancement method to high-definition video, scale-down video of high-definition video is used and the parameter for image enhancement method is computed from small size video. To enhance the color of high-definition video, we apply color constancy method. First, we separate the video into several scenes by cut detection method. Then, we apply color constancy to each scene with same parameter. To improve the contrast of high-definition video, we use union of original image and histogram equalized image, and weight is calculated based on sorting of histogram bins. Finally, the performance of proposed method is demonstrated in experiment section.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.905-923
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• 2018

In order to generate high-resolution products using UAV images, it is necessary to analyze the sharpness of the themselves measured through image analysis. When images that have unclear sharpness of UAV are used in the production, they can have a great influence on operations such as acquisition and mapping of accurate three-dimensional information using UAV. GRD (Ground Resolved Distance) has been used as an indicator of image clarity. GRD is defined as the minimum distance between two identifiable objects in an image and is used as a concept against the GSD (Ground Sampling Distance), which is a spatial sample interval. In this study, GRD is extracted by analyzing the edge target without visual analysis. In particular, GRD to GSD ratio (GRD/GSD), or GRD expressed in pixels, is used as an index for evaluation the relative image sharpness. In this paper, GRD is calculated by analyzing edge targets at various altitudes in various shooting environments using a rotary wing. Using GRD/GSD, it was possible to identify images whose sharpness was significantly lowered, and the appropriateness of the image as an image clarity index was confirmed.