The Experts below are selected from a list of 7116 Experts worldwide ranked by ideXlab platform
Tao Sun - One of the best experts on this subject based on the ideXlab platform.
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Robust non-local fuzzy c-means algorithm with Edge Preservation for SAR image segmentation
Signal Processing, 2013Co-Authors: Jie Feng, Licheng Jiao, Xiangrong Zhang, Maoguo Gong, Tao SunAbstract:Fuzzy c-means (FCM) algorithm has been proven effective for image segmentation; nevertheless it is sensitive to different types of noises. Up to now, a series of improved FCM algorithms incorporating spatial information have been developed, which are robust for Gaussian, uniform, and salt and pepper noises. However, limited effort has been placed on tackling the problem of a large amount of intrinsic and undesired multiplicative speckle in synthetic aperture radar (SAR) images. A crucial problem for SAR image segmentation is to guarantee speckle insensitiveness and Edge detail Preservation simultaneously. To address this problem, a robust and specific non-local FCM algorithm with Edge Preservation for SAR image segmentation is proposed. In this study, a new image is constructed using the non-local information and rectifying the Edge parts, which is robust for speckle without sacrificing Edge sharpness. To measure the patch-similarity in non-local method effectively, a novel generalized ratio distance based on SAR multiplicative speckle is defined. To locate and rectify the Edge parts, coefficient of variation (CV) based threshold and orientation based statistics methods are designed. At last, this new image is clustered by FCM algorithm. Compared with six improved FCM algorithms and two state-of-the-art segmentation algorithms (spectral clustering and normalized cuts), the proposed algorithm obtains the best performance in terms of region uniformity and boundary localization.
Xiuchang Zhu - One of the best experts on this subject based on the ideXlab platform.
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single image super resolution method based on Edge Preservation
International Conference on Image and Graphics, 2011Co-Authors: Yaqiong Fan, Zongliang Gan, Yiwen Qiu, Xiuchang ZhuAbstract:In this paper, we present a novel super resolution (SR) framework based on Edge Preservation. The iterative back-projection algorithm (IBP) is a classical SR method and has low computational complexity, which can be applied in real time applications. However, it often produces many artifacts especially along the strong Edges. To reduce the jaggy artifacts, our approach has three steps. First, we improve the initial estimate using bilateral filtering to strengthen the true Edges. Second, we learn the structural content of low resolution pixel and the correlation among the pixels with similar structure. Third, we use the correlation to guide the output image reconstructed by the IBP algorithm. The experimental result proved that our proposed method can remove the artifacts and obtain clear and sharp Edges in visual perception.
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ICIG - Single Image Super Resolution Method Based on Edge Preservation
2011 Sixth International Conference on Image and Graphics, 2011Co-Authors: Yaqiong Fan, Zongliang Gan, Yiwen Qiu, Xiuchang ZhuAbstract:In this paper, we present a novel super resolution (SR) framework based on Edge Preservation. The iterative back-projection algorithm (IBP) is a classical SR method and has low computational complexity, which can be applied in real time applications. However, it often produces many artifacts especially along the strong Edges. To reduce the jaggy artifacts, our approach has three steps. First, we improve the initial estimate using bilateral filtering to strengthen the true Edges. Second, we learn the structural content of low resolution pixel and the correlation among the pixels with similar structure. Third, we use the correlation to guide the output image reconstructed by the IBP algorithm. The experimental result proved that our proposed method can remove the artifacts and obtain clear and sharp Edges in visual perception.
Jie Feng - One of the best experts on this subject based on the ideXlab platform.
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Robust non-local fuzzy c-means algorithm with Edge Preservation for SAR image segmentation
Signal Processing, 2013Co-Authors: Jie Feng, Licheng Jiao, Xiangrong Zhang, Maoguo Gong, Tao SunAbstract:Fuzzy c-means (FCM) algorithm has been proven effective for image segmentation; nevertheless it is sensitive to different types of noises. Up to now, a series of improved FCM algorithms incorporating spatial information have been developed, which are robust for Gaussian, uniform, and salt and pepper noises. However, limited effort has been placed on tackling the problem of a large amount of intrinsic and undesired multiplicative speckle in synthetic aperture radar (SAR) images. A crucial problem for SAR image segmentation is to guarantee speckle insensitiveness and Edge detail Preservation simultaneously. To address this problem, a robust and specific non-local FCM algorithm with Edge Preservation for SAR image segmentation is proposed. In this study, a new image is constructed using the non-local information and rectifying the Edge parts, which is robust for speckle without sacrificing Edge sharpness. To measure the patch-similarity in non-local method effectively, a novel generalized ratio distance based on SAR multiplicative speckle is defined. To locate and rectify the Edge parts, coefficient of variation (CV) based threshold and orientation based statistics methods are designed. At last, this new image is clustered by FCM algorithm. Compared with six improved FCM algorithms and two state-of-the-art segmentation algorithms (spectral clustering and normalized cuts), the proposed algorithm obtains the best performance in terms of region uniformity and boundary localization.
Yaqiong Fan - One of the best experts on this subject based on the ideXlab platform.
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single image super resolution method based on Edge Preservation
International Conference on Image and Graphics, 2011Co-Authors: Yaqiong Fan, Zongliang Gan, Yiwen Qiu, Xiuchang ZhuAbstract:In this paper, we present a novel super resolution (SR) framework based on Edge Preservation. The iterative back-projection algorithm (IBP) is a classical SR method and has low computational complexity, which can be applied in real time applications. However, it often produces many artifacts especially along the strong Edges. To reduce the jaggy artifacts, our approach has three steps. First, we improve the initial estimate using bilateral filtering to strengthen the true Edges. Second, we learn the structural content of low resolution pixel and the correlation among the pixels with similar structure. Third, we use the correlation to guide the output image reconstructed by the IBP algorithm. The experimental result proved that our proposed method can remove the artifacts and obtain clear and sharp Edges in visual perception.
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ICIG - Single Image Super Resolution Method Based on Edge Preservation
2011 Sixth International Conference on Image and Graphics, 2011Co-Authors: Yaqiong Fan, Zongliang Gan, Yiwen Qiu, Xiuchang ZhuAbstract:In this paper, we present a novel super resolution (SR) framework based on Edge Preservation. The iterative back-projection algorithm (IBP) is a classical SR method and has low computational complexity, which can be applied in real time applications. However, it often produces many artifacts especially along the strong Edges. To reduce the jaggy artifacts, our approach has three steps. First, we improve the initial estimate using bilateral filtering to strengthen the true Edges. Second, we learn the structural content of low resolution pixel and the correlation among the pixels with similar structure. Third, we use the correlation to guide the output image reconstructed by the IBP algorithm. The experimental result proved that our proposed method can remove the artifacts and obtain clear and sharp Edges in visual perception.
Don Stredney - One of the best experts on this subject based on the ideXlab platform.
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Edge Preservation in volume rendering using splatting
Symposium on Volume Visualization, 1998Co-Authors: Jian Huang, Roger Crawfis, Don StredneyAbstract:The paper presents a method to preserve sharp Edge details in splatting for volume rendering. Conventional splatting algorithms produce fuzzy images for views close to the volume model. The lack of details in such views greatly hinders study and manipulation of data sets using virtual navigation. Our method applies a nonlinear warping to the footprints of conventional splat and builds a table of footprints for different possible Edge positions and Edge strengths. When rendering, we pick a footprint from the table for each splat, based on the relative position of the voxel to the closest Edge. Encouraging results have been achieved both for synthetic data and medical data.
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VVS - Edge Preservation in volume rendering using splatting
Proceedings of the 1998 IEEE symposium on Volume visualization - VVS '98, 1998Co-Authors: Jian Huang, Roger Crawfis, Don StredneyAbstract:The paper presents a method to preserve sharp Edge details in splatting for volume rendering. Conventional splatting algorithms produce fuzzy images for views close to the volume model. The lack of details in such views greatly hinders study and manipulation of data sets using virtual navigation. Our method applies a nonlinear warping to the footprints of conventional splat and builds a table of footprints for different possible Edge positions and Edge strengths. When rendering, we pick a footprint from the table for each splat, based on the relative position of the voxel to the closest Edge. Encouraging results have been achieved both for synthetic data and medical data.
