• 제목/요약/키워드: Texture approximation

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질감 근사화 및 반복적 병합을 이용한 율왜곡 기반 영상 분할 (Rate-Distortion Based Image Segmentation Using Recursive Merging and Texture Approximation)

  • 정춘식;임채환;김남철
    • 한국통신학회논문지
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    • 제25권1B호
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    • pp.156-166
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    • 2000
  • 본 논문에서는 반복적 병합의 율왜곡 기반 비용을 계산할 때 일반화된 질감 근사화 과정을 도입함으로써 질감 특성이 고려된 율왜곡 기반 영상 분할 기법을 제시하였다. 이때 영역 내부의 질감은 SA-DCT를 적용한 후, 양자화 간격이 고정된 두 개의 균일 양자화기에 의해 DC 성분 및 AC 성분을 각각 근사화하여 율왜곡 기반 비용을 구하고, 이러한 율왜곡 기반 비용에 근거하여 반복적 병합을 이용한 영상 분할을 수행하였다. 256$\times$256 Lena에 대하여 실험한 결과, 제안한 분할법에 의한 영역기반 부호화는 DC 성분만으로 근사화하여 율왜곡 기반 영상분할에 의한 것과 JPEG에 비하여 각각 0.8~1.0 ㏈, 1.2~1.5㏈ 정도의 PSNR 성능 개선이 있는 것으로 나타났다.

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A Fast Algorithm for Region-Oriented Texture Coding

  • Choi, Young-Gyu;Choi, Chong-Hwan;Cheong, Ha-Young
    • 한국정보전자통신기술학회논문지
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    • 제9권6호
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    • pp.519-525
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    • 2016
  • This paper addresses the framework of object-oriented image coding, describing a new algorithm, based on monodimensional Legendre polynomials, for texture approximation. Through the use of 1D orthogonal basis functions, the computational complexity which usually makes prohibitive most of 2D region-oriented approaches is significantly reduced, while only a slight increment of distortion is introduced. In the aim of preserving the bidimensional intersample correlation of the texture information as much as possible, suitable pseudo-bidimensional basis functions have been used, yielding significant improvements with respect to the straightforward 1D approach. The algorithm has been experimented for coding still images as well as motion compensated sequences, showing interesting possibilities of application for very low bitrate video coding.

영역화에 기초를 둔 영상 부호화에서 영역 부호화 방법의 개선에 관한 연구 (A Study on the Improvement of Texture Coding in the Region Growing Based Image Coding)

  • 김주은;김성대;김재균
    • 대한전자공학회논문지
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    • 제26권6호
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    • pp.89-96
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    • 1989
  • 본 논문에서는 영역화에 기초를 둔 영상 부호화의 한 부분인 영역 부호화의 개선에 관한 연구가 수행되었다. 영역화시 texture의 효율적인 표현을 위하여 영상을 stochastic random field로 묘사 될 수 있는 stochastic 영역과 non-stochastic 영역으로 구분한다. 영역 부호화 및 복원시 stochastic 영역에 대해서는 autoregressive model을 이용하고 non-stochastic영역은 2차원 다항식 근사화를 이용한다. 제안 방식은 2차원 다항식 근사화만을 이용한 기존 방식보다 더 좋은 주관적 화질을 가지며, 상대적인 data 감축할 수 있었고 영상의 부호화 및 복원에 필요한 수행시간을 단축시켰다.

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3차원 물체의 형상 인식에 관한 연구 (A Study on Shape from Patterns)

  • 김도년;조동섭
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1990년도 하계학술대회 논문집
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    • pp.542-545
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    • 1990
  • Texture provides an important source of information about the local orientation of visible surfaces. In this study the 3D shape of a textured surface is recovered from its perspective projection image on the assumption that the texture is homogeneously distributed. To recover 3D structure, the distorting effects of the perspective projection must be distinguished from properties of the texture. In this study, paraperspective projection, approximation of perspective projection, has employed.

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밝기 왜곡을 고려한 윤곽선 근사화용 정점 선택 방법 (Vertex selection method considering texture degradation for contour approximation)

  • 최재각;이시웅;고창림;이종극
    • 방송공학회논문지
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    • 제10권4호통권29호
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    • pp.632-642
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    • 2005
  • 본 논문에서는 다각형 기반 윤곽선 근사화를 위한 새로운 정점 선택 방법을 제안한다. 제안 방법은 전체 윤곽선을 부분 윤곽선으로 분할하고, 분할된 각 부분 윤곽선을 가변적 정확도에 따라 적응적으로 근사화한다. 근사화 정확도는 각 부분 윤곽선의 상대적 중요도에 의해 결정된다. 이때 근사화 오차 영역에서 발생하는 밝기 왜곡을 고려하여 각 부분 윤곽선의 상대적 중요도를 결정함으로써, 같은 윤곽선 데이터 량으로 보다 높은 재생영상의 화질 향상을 이룰 수 있다. 이러한 개념을 바탕으로 영역간 대조와 최대허용오차($d_{max}$)와의 관계식을 유도하고, 이 식을 이용한 적응적 정점 선택 방법을 제안한다. 실험 결과, 제안된 방법이 영상 부호화의 측면에서 기존 기법보다 우수한 성능을 나타내었다.

블록단위의 프래탈 근사화를 이용한 영상코딩 (Image Coding by Block Based Fractal Approximation)

  • 정현민;김영규;윤택현;강현철;이병래;박규태
    • 전자공학회논문지B
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    • 제31B권2호
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    • pp.45-55
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    • 1994
  • In this paper, a block based image approximation technique using the Self Affine System(SAS) from the fractal theory is suggested. Each block of an image is divided into 4 tiles and 4 affine mapping coefficients are found for each tile. To find the affine mapping cefficients that minimize the error between the affine transformed image block and the reconstructed image block, the matrix euation is solved by setting each partial differential coefficients to aero. And to ensure the convergence of coding block. 4 uniformly partitioned affine transformation is applied. Variable block size technique is employed in order to applynatural image reconstruction property of fractal image coding. Large blocks are used for encoding smooth backgrounds to yield high compression efficiency and texture and edge blocks are divided into smaller blocks to preserve the block detail. Affine mapping coefficinets are found for each block having 16$\times$16, 8$\times$8 or 4$\times$4 size. Each block is classified as shade, texture or edge. Average gray level is transmitted for shade bolcks, and coefficients are found for texture and edge blocks. Coefficients are quantized and only 16 bytes per block are transmitted. Using the proposed algorithm, the computational load increases linearly in proportion to image size. PSNR of 31.58dB is obtained as the result using 512$\times$512, 8 bits per pixel Lena image.

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Graphical Video Representation for Scalability

  • Jinzenji, Kumi;Kasahara, Hisashi
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송공학회 1996년도 Proceedings International Workshop on New Video Media Technology
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    • pp.29-34
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    • 1996
  • This paper proposes a new concept in video called Graphical Video. Graphical Video is a content-based and scalable video representation. A video consists of several elements such as moving images, still images, graphics, characters and charts. All of these elements can be represented graphically except moving images. It is desirable to transform these moving images graphical elements so that they can be treated in the same way as other graphical elements. To achieve this, we propose a new graphical representation of moving images using spatio-temporal clusters, which consist of texture and contours. The texture is described by three-dimensional fractal coefficients, while the contours are described by polygons. We propose a method that gives domain pool location and size as a means to describe cluster texture within or near a region of clusters. Results of an experiment on texture quality confirm that the method provides sufficiently high SNR as compared to that in the original three-dimensional fractal approximation.

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영상 영역화를 이용한 영상 부호화 기법 (An Image Coding Technique Using the Image Segmentation)

  • 정철호;이상욱;박래홍
    • 대한전자공학회논문지
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    • 제24권5호
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    • pp.914-922
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    • 1987
  • An image coding technique based on a segmentation, which utilizes a simplified description of regions composing an image, is investigated in this paper. The proposed coding technique consists of 3 stages: segmentation, contour coding. In this paper, emphasis was given to texture coding in order to improve a quality of an image. Split-and-merge method was employed for a segmentation. In the texture coding, a linear predictive coding(LPC), along with approximation technique based on a two-dimensional polynomial function was used to encode texture components. Depending on a size of region and a mean square error between an original and a reconstructed image, appropriate texture coding techniques were determined. A computer simulation on natural images indicates that an acceptable image quality at a compression ratio as high as 15-25 could be obtained. In comparison with a discrete cosine transform coding technique, which is the most typical coding technique in the first-generation coding, the proposed scheme leads to a better quality at compression ratio higher than 15-20.

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Texture Analysis and Classification Using Wavelet Extension and Gray Level Co-occurrence Matrix for Defect Detection in Small Dimension Images

  • Agani, Nazori;Al-Attas, Syed Abd Rahman;Salleh, Sheikh Hussain Sheikh
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2004년도 ICCAS
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    • pp.2059-2064
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    • 2004
  • Texture analysis is an important role for automatic visual insfection. This paper presents an application of wavelet extension and Gray level co-occurrence matrix (GLCM) for detection of defect encountered in textured images. Texture characteristic in low quality images is not to easy task to perform caused by noise, low frequency and small dimension. In order to solve this problem, we have developed a procedure called wavelet image extension. Wavelet extension procedure is used to determine the frequency bands carrying the most information about the texture by decomposing images into multiple frequency bands and to form an image approximation with higher resolution. Thus, wavelet extension procedure offers the ability to robust feature extraction in images. Then the features are extracted from the co-occurrence matrices computed from the sub-bands which performed by partitioning the texture image into sub-window. In the detection part, Mahalanobis distance classifier is used to decide whether the test image is defective or non defective.

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Image Restoration and Object Removal Using Prioritized Adaptive Patch-Based Inpainting in a Wavelet Domain

  • Borole, Rajesh P.;Bonde, Sanjiv V.
    • Journal of Information Processing Systems
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    • 제13권5호
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    • pp.1183-1202
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    • 2017
  • Image restoration has been carried out by texture synthesis mostly for large regions and inpainting algorithms for small cracks in images. In this paper, we propose a new approach that allows for the simultaneous fill-in of different structures and textures by processing in a wavelet domain. A combination of structure inpainting and patch-based texture synthesis is carried out, which is known as patch-based inpainting, for filling and updating the target region. The wavelet transform is used for its very good multiresolution capabilities. The proposed algorithm uses the wavelet domain subbands to resolve the structure and texture components in smooth approximation and high frequency structural details. The subbands are processed separately by the prioritized patch-based inpainting with isophote energy driven texture synthesis at the core. The algorithm automatically estimates the wavelet coefficients of the target regions of various subbands using optimized patches from the surrounding DWT coefficients. The suggested performance improvement drastically improves execution speed over the existing algorithm. The proposed patch optimization strategy improves the quality of the fill. The fill-in is done with higher priority to structures and isophotes arriving at target boundaries. The effectiveness of the algorithm is demonstrated with natural and textured images with varying textural complexions.