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Image Denoising Based on the Wavelet Co-Occurrence Matrix
Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005., 2006Image denoising is a well-known problem in signal processing. Wavelet decomposition based approaches have been applied successfully to the image denoising problem. The majority of wavelet thresholding methods do not take the spatial correlation between wavelet coefficients into account.
null Zeyong Shan, S. Aviyente
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Robust skin-roughness estimation based on co-occurrence matrix
Journal of Visual Communication and Image Representation, 2017Abstract As the interest in one’s appearance has recently increased, the demand for diagnosing skin conditions has also increased. However, conventional specialized skin diagnostic devices are generally expensive, and people have to visit a skin-care shop to diagnose their skin condition. This is time consuming and troublesome.
Ji-Sang Bae +3 more
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Fractal Dimension Co-occurrence Matrix Method for Texture Classification
TENCON 2006 - 2006 IEEE Region 10 Conference, 2006The fractal dimension co-occurrence matrix (FDCM) method, incorporating with fractal dimension and the gray level co-occurrence matrix (GLCM) method, is presented for texture classification. 12 Brodatz's natural texture images were classified by the GLCM method, sub-band domain co-occurrence matrix (SBCM) method and the FDCM method.
Ju Hyun Kim, Soo Chang Kim, Tae Jin Kang
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Image Retrieval Using Modified Color Variation Co-occurrence Matrix
2008Texture is widely used as an important feature for content based image retrieval (CBIR). In this paper, color variation co-occurrence matrix (CVCM) modified from a previous investigation has been proposed for describing texture characteristics of an image.
Yung-Fu Chen +5 more
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The co-occurrence matrix in square and hexagonal lattices
7th International Conference on Control, Automation, Robotics and Vision, 2002. ICARCV 2002., 2004There are many situations where processing of images on alternate lattices can yield positive advantages. One such case is processing of images upon hexagonal lattices where the uniform connectivity can lead to many efficiencies. However, before processing can be evaluated on hexagonal lattices it must be ascertained that fundamental operations can be ...
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Template matching with multi-feature co-occurrence matrix
Optics and Precision Engineering, 2021Su-peng JIANG +3 more
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Illumination Invariant Texture Classification with Pattern Co-occurrence Matrix
2011A new illumination invariant feature extraction method for texture classification is proposed. In order to capture the local image texture, texture pattern transform (TPT) in a local neighborhood of a monochrome texture image is introduced. The TPT is robust against any monotonic transformation of the gray scale.
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3D Shape Representation Using Gaussian Curvature Co-occurrence Matrix
2010Co-occurrence matrix is traditionally used for the representation of texture information. In this paper, the co-occurrence matrix is combined with Gaussian curvature for 3D shape representation and a novel 3D shape description approach named Gaussian curvature co-occurrence matrix is proposed.
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