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칼라 영상 예측 부호화를 위한 객체 기반 스펙트럴 상관성 추정 기법
곽노윤,황병원 한국항공대학교 1999 論文集 Vol.37 No.-
본 논문은 칼라 성분 영상들 간에 내재된 스펙트럴 중복성에 착안하여 움직임 추정과 유사하게 한 성분 영상에서 다른 성분 영상을 영역 기반으로 예측 부호화함으로써 칼라 영상 부호화 시에 고압축을 실현할 수 있도록 한 영역 기반 칼라 영상 예측 부호화에 관한 것이다. 우선, 각 칼라 성분들간의 색차 성분을 화소 단위로 합산한 색차합 영상을 산출한 후, 색차합 영상을 대상으로 영역 분할을 수행한다. 이후, R, G, B 영상 중에서 임의로 선정한 두 칼라 성분 영상에 대해 휘도 영상과 각 칼라 성분 영상간의 추정 오차가 최소가 되도록 하는 비례 인자와 가감 이자를 객채 영역당 하나씩 산출하는 과정을 반복적으로 수행한 후, 이렇게 추정한 각각의 비례인자와 가감 인자를 부호화함으로써 칼라 성분을 추정 부호화할 수 있는 새로운 칼라 영상 부호화 방법을 제안한다. 시뮬레이션 결과를 통해 같은 PSNR에서 두 칼라 성분 영상을 부호화하기 위해 소요되는 단위 화소당 비트를 비교해 볼때, 제안된 칼라 영상 부호화 방법은 DCT 기반칼라 영상 압축 방법에 비해 수십 배 정도의 추가적인 압축 효과를 제공함을 확인할 수 있었다. This paper is relates to a new color image coding method for predictively encoding color image by estimating object-based spectral correlation, and particularly to predictive color image coding which estimates one component image from other component image for removing spectral redundancy included between color component images. First, chroma-summation image between color component images is obtained, and then for segmenting the object region which is the unit for estimating spectral correlation, image segmentation for chroma-summation image is performed. Next, the step calculating a scale factor and a offset factor for each the object capable of minimizing the estimation error between luminance image Y and each color component image, is iteratively applied to two color component images arbitrarily selected among R, G and B images. In the computer simulation, the proposed coding method provides the compression ratio being the maximum several tens times higher than DCT-based color component image coding method in aspect of bpp required to encode two color component images for the same PSNR
Skinny Smudge Blending Based on Master Shape Segmentation
No-Yoon Kwak,Eun-Young Ahn 한국콘텐츠학회 2009 ICCC International Digital Design Invitation Exhib Vol.2009 No.12
This paper is related to a skinny smudge blending based on the image segmentation for a master shape. The smudge tool is the popular graphic tool embedded in Adobe Photoshop. The smudge tool is used to smear paint on your canvas. The effect is much like finger painting. You can use the smudge tool by clicking on the smudge icon and clicking on the canvas and while holding the mouse button down, dragging in the direction you want to smudge. A disadvantage of previous smudge tool is to also smear pixels in the undesired region according to generating the target image as blending all pixels in a diameter of the master. In this paper to reduce the disadvantage, the skinny smudge blending based on the image segmentation for a master shape is proposed. The proposed skinny smudge blending has the advantage of applying the smudge effect to the desired regions regardless of the background as the master shape adhered closely to the contour shape is extracted by color image segmentation.
Semi-automatic Field Morphing : Polygon-based Vertex Selection and Adaptive Control Line Mapping
Kwak, No-Yoon The Korea Contents Association 2007 International Journal of Contents Vol.3 No.4
Image morphing deals with the metamorphosis of one image into another. The field morphing depends on the manual work for most of the process, where a user has to designate the control lines. It takes time and requires skills to have fine quality results. It is an object of this paper to propose a method capable of realizing the semi-automation of field morphing using adaptive vertex correspondence based on image segmentation. The adaptive vertex correspondence process efficiently generates a pair of control lines by adaptively selecting reference partial contours based on the number of vertices that are included in the partial contour of the source morphing object and in the partial contour of the destination morphing object, in the pair of the partial contour designated by external control points through user input. The proposed method generates visually fluid morphs and warps with an easy-to-use interface. According to the proposed method, a user can shorten the time to set control lines and even an unskilled user can obtain natural morphing results as he or she designates a small number of external control points.
공유된 초기 영상에 기반한 무반복 프랙탈 복호 알고리즘
곽노윤(Kwak No-Yoon),한군희(Han Kun-Hee) 한국콘텐츠학회 2003 한국콘텐츠학회 종합학술대회 논문집 Vol.1 No.2
Jacquin에 의해 프랙탈 이론을 이용한 영상 부호화 기법이 소개된 이래로, Fisher와 Beaumont 등에 의하여 낮은 비트율에서도 우수한 화지을 제공하는 프랙탈 영상 압축 기법들이 다수 제안되었다. 그러나 기존에 고안된 기법들이 갖고 있는 하나의 문제점은 복호화가 반복 처리를 통해 구현되며 그 복잡도가 각각의 영상에 따라 상이하다는 것이다. 본 논문에서는 복호 시간을 단축시키기 위해 반복 변환이 필요없는 프랙탈 영상 복호 알고리즘을 제안하고자 한다. 제안된 방법은 복호기에서 사용할 초기 영상과 동일한 코드북 영상을 부호기에 보유하고 있는 상태에서 부호화 과정에서는 이 코드북 영상과 부호화하려는 영상의 유사성을 찾아 프랙탈 계수를 구한다. 이후, 복호화 과정에서는 수신된 프팩탈 계수와 기설정된 초기 영상을 이용하여 반복 변환 없이 한 번에 영상을 복호함으로써 보호 시간을 현저하게 단축시킬 수 있었다. Since Jacquine introduced the image coding algorithm using fractal theory, many fractal image compression algorithms providing good quality at low bit rate have been proposed by Fisher and Beaumount et al.. But a problem of the previous implementations is that the decoding rests on an iterative procedure whose complexity is image-dependent. This paper proposes an iterative-free fractal image decoding algorithm to reduce the decoding time. In the proposed method, under the encoder previously with the same codebook image as an initial image to be used at the decoder, the fractal coefficients are obtained through calculating the similarity between the codebook image and a input image to be encoded. As the decoding process can be completed with received fractal coefficients and predefined initial image without repeated iterations, the decoding time could be remarkably reduced.
곽노윤(Kwak No Yoon),황병원(Hwang Byong Won) 한국정보처리학회 1999 정보처리학회논문지 Vol.6 No.8
In this paper, a variable motion estimation scheme based on HBMA(Hierarchical Block Matching Algorithm) to improve the performance and to reduce heavy computational and transmission load, is presented. The proposed algorithm is composed of four steps. First, block activity for each block is defined using the edge information of differential image between two sequential images, and then average block activity of the present image is found by taking the mean of block activity. Secondly, camera pan compensation is carried out, according to the average activity of the image, in the hierarchical pyramid structure constructed by wavelet transform. Next, the LUT classifying each block into one among Moving, No Moving, Semi-Moving Block according to the block activity compensated camera pan is obtained. Finally, as varying the block size and adaptively selecting the initial search layer and the search range referring to LUT, the proposed variable HBMA can effectively carries out fast motion estimation in the hierarchical pyramid structure. The cost function needed above-mentioned each step is only the block activity defined by the edge information of the differential image in the sequential images.