• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.345-348
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• 2001

본 논문에서는 변이-움직임 벡터의 상관관계를 통한 동시 추정(joint disparity and motion estimation)을 이용하여 방대한 계산량과 데이터량을 요구하는 스테레오 영상 데이터의 효율적인 부호화를 위한 알고리즘을 제안한다. 스테레오 시퀀스에 대해서 두 변이 벡터(disparity vector)와 하나의 움직임 벡터(motion vector)의 상관관계를 이용하면 나머지 움직임 벡터는 직접적인 추정 과정 없이 얻을 수 있다. 하지만, 이렇게 얻어진 움직임 벡터는 직접 추정에 비해 정확도가 현저히 떨어져 이 벡터를 그대로 사용하여 영상을 복원하게 될 경우 심각한 오차의 누적이 발생한다. 따라서 본 논문에서는 효율적인 동시 추정을 위해 추정단에서 벡터 평활화(vector regularization)과정을 수행하고 불확실 벡터 영역 추출을 통한 선택적인 보정 과정을 수행한다. 또한, 불확실 벡터 영역의 벡터만을 가변장 부호화(variable length coding)한다. 실험결과, 직접 추정 과정을 거치지 않고 도 만족할 만한 화질의 영상을 얻을 수 있었으며, 부호화량도 상당히 감소시킬 수 있었다.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.713-716
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• 2000

본 논문에서는 프레임간 압축 영상의 열화 과정의 모델과, 동영상에 존재하는 블록화 현상을 제거하는 방법을 제안한다 BDCT기반으로 압축된 정지영상은 DCT계수를 양자화 하는 과정이 블록별로 처리되기 때문에, 블록 경계에 불연속이 발생한다. 동영상의 경우 블록 경계에서 불연속이 발생 할 뿐만 아니라 움직임 보상과정이 합쳐진 혼성 구조로 되어 있어서 블록 내부에서도 불연속이 존재하게 된다. 블록 영계만을 생각한 기존의 처리방법은 동영상의 처리에 있어 적합하지 못하다. 따라서 본 논문에서는 효율적인 블록화 현상 제거를 위해, 양방향 움직임 보상과 반화소 정밀도를 이용한 새로운 평활화 제약조건을 구성하고 차분 영역에서의 정규화 방법을 이용한 알고리듬을 제안한다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.11a
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• pp.283-286
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• 2014

X-ray 영상의 경우 검은 배경으로 인해 기존의 히스토그램 평활화를 사용하여 대비비를 향상 시킬 경우 문제가 발생한다. 전역 히스토그램 평활화의 경우 영상의 특징을 고려하지 않은 채 전체적으로 히스토그램 평활화가 이루어지기 때문에 부분적인 명암값을 개선시키기 어렵다. BBHE(Bright Preserving Bi-Histogram Equalization)과 DSIHE(Dualistic Sub-Image Histogram Equalization)과 같은 영역별 히스토그램 평활화의 경우 X-ray 사진특성상 검은 배경으로 인하여 히스토그램 평활화를 적용해도 원하는 대비비를 얻기 힘들며 부분적으로 왜곡이 발생한다. 이러한 문제를 해결하기 위해 본 논문에서는 영상의 히스토그램을 통해 배경 정보를 파악하여 밝기 영역을 나눈 후 히스토그램 평활화를 진행함으로써 X-ray 사진의 대비비를 효율적으로 향상시킨다.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.4
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• pp.611-617
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• 2004

Pixel classification is one of basic image processing issues. The general characteristics of the pixels belonging to various classes are discussed and the radical principles of pixel classification are given. At the same time. a pixel classification scheme based on image direction measure is proposed. As a typical application instance of pixel classification, an adaptive multi-level median filter is presented. An image can be classified into two types of areas by using the direction information measure, that is. smooth area and edge area. Single direction multi-level median filter is used in smooth area. and multi-direction multi-level median filter is taken in the other type of area. What's more. an adaptive mechanism is proposed to adjust the type of the filters and the size of filter window. As a result. we get a better trade-off between preserving details and noise filtering.

• Journal of the Korea Computer Industry Society
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• v.3 no.7
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• pp.871-880
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• 2002

In this paper, I proposed the adaptive watermarking based on the discrete wavelet transform for the very robust watermarking against intentional distortion which attacks on image. A watermark is an binary image such as document(sign), and such watermark image is embedded in the LH and HL band of wavelet transformed domain for copyright protection of image data. To evaluate robustness of the proposed method, we applied some basic algorithm of image processing such as brightening, darkening, sharpening, blurring, cropping, histogram equalizing and lossy compression(JPEG, gif). As a result of experiment, the proposed method has the good image quality and the high perceptibility of watermark. It was demonstrated by experiments that the proposed algorithm can provide an excellent protection under various attacks.

• Journal of Broadcast Engineering
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• v.22 no.5
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• pp.608-617
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• 2017

Methods of contrast enhancement have problem such as side effect of over-enhancement with non-gaussian histogram distribution, tradeoff enhancement efficiency against brightness preserving. In order to enhance contrast at various histogram distribution, segmentation to region with gaussian distribution and then enhance contrast each region. First, we segment an image into several regions using GMM(Gaussian Mixture Model)fitting by that k-mean clustering and EM(Expectation-Maximization) in $L^*a^*b^*$ color space. As a result region segmentation, we get the region map and probability map. Then we apply local contrast enhancement algorithm that mean shift to minimum overlapping of each region and preserve brightness histogram equalization. Experiment result show that proposed region based contrast enhancement method compare to the conventional method as AMBE(AbsoluteMean Brightness Error) and AE(Average Entropy), brightness is maintained and represented detail information.

• Journal of Internet Computing and Services
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• v.3 no.6
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• pp.13-24
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• 2002

This paper presents an automatic approach to detect face and facial feature from face images based on the color information and deformable model. Skin color information has been widely used for face and facial feature diction since it is effective for object recognition and has less computational burden, In this paper, we propose how to compensates varying light condition and utilize the transformed YCbCr color model to detect candidates region of face and facial feature from color images, Moreover, the detected face facial feature areas are subsequently assigned to a initial condition of active contour model to extract optimal boundaries of face and facial feature by resolving initial boundary problem when the active contour is used, The experimental results show the efficiency of the proposed method, The face and facial feature information will be used for face recognition and facial feature descriptor.

• Journal of the Korean earth science society
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• v.30 no.7
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• pp.834-844
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• 2009

Two-dimensional magnetotelluric (MT) inversion algorithm using minimum support (MS) stabilizer functional was implemented in this study to enhance the contrast of inverted images. For this implementation, this study derived a formula in discrete form for creeping model updates in the least-squares linearized inversion. A spatially varying regularization parameter determination algorithm, which is known as ACB (Active Constraint Balancing), was also adopted to stabilize the inversion process when using MS stabilizer as a model constraint. Inversion experiments for a simple isolated body model show well the feature of MS stabilizer in concentrating the anomalous body compared with the second-order derivative model constraint. This study also compared MS stabilizer and the second-order derivative model constraints for a model having multiple anomalous bodies to show the applicability of the algorithm into field data.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.4
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• pp.49-55
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• 2010

Cast shadow caused by an illumination condition can produce troublesome effects for face recognition system using reflectance image. Consequently, we need to separate cast shadow area from feature area for improvement of recognition accuracy. A Bilateral filter smooths image while preserving edges, by means of a nonlinear combination of nearby pixel values. Processing such characteristics, this method is suited to our purpose in illumination estimation process based on Retinex. Therefore, in this paper, we propose a new illumination normalization method based on the Bilateral filter in face images. The proposed method produces a reflectance image that is preserved relatively exact cast shadow area, because coefficient of filter is designed to multiply proximity and discontinuity of pixels in input image. Performance of our method is measured by a recognition accuracy of principle component analysis(PCA) and evaluated to compare with other conventional illumination normalization methods.

• Proceedings of the Korean Society of Computer Information Conference
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• 2016.07a
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• pp.295-296
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• 2016

본 연구에서는 LED 광 자극이 뇌의 어느 영역을 자극하여 신경신호를 전달하는지에 관해서 관찰하고자 연구를 진행하였다. 광 자극에 의한 뇌 영역의 활성변화를 관찰하기 위하여 실험용 소동물과 영상장비인 9.4T MRI를 이용하여 연구를 수행 하였다. 실험용 소동물은 Balb/c 마우스를 이용하였으며 기능적 자기공명영상 획득 방법 중 하나인 에코평면영상 기법을 이용하여 뇌 영상을 획득 하였다. 획득한 영상을 바탕으로 뇌 영역의 자극 정도를 확인해보기 위해 영상처리기법인 재편성(realignment), 일치(co-registration), 표준화(normalization), 평활화(smoothing) 방법으로 영상을 전처리 하고, statistical parametric map (SPM12)을 사용하여 분석하였다. 본 연구에서는 광자극이 소동물 뇌 영역 중 하나인 상구(Superior colliculus)영역과 대뇌의 시각피질 (visual cortex, V1) 영역에서 자극을 일으키는 것을 확인할 수 있었다.