The Experts below are selected from a list of 321 Experts worldwide ranked by ideXlab platform
Qionghai Dai - One of the best experts on this subject based on the ideXlab platform.
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deblur a blurred rgb image with a sharp nir image through local Linear Mapping
International Conference on Multimedia and Expo, 2014Co-Authors: Tao Yue, Mingting Sun, Zhengyou Zhang, Jinli Suo, Qionghai DaiAbstract:Image acquisition in a low light environment requires long exposure to achieve acceptable signal-to-noise ratio, which however causes blurry effect. This paper addresses this problem by using a sharp near-infrared (NIR) image when the environment has sufficient NIR light. We assume that an RGB and NIR image pair has a Linear Mapping in a local area and that the Mapping function is valid for both the blur and sharp image pairs. Using this property, we solve the sharp RGB images from a blurred RGB image and the corres ponding s harp NIR image. The effectiveness of the proposed algorithm is verified with both synthetic and real captured datasets.
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ICME - Deblur a blurred RGB image with a sharp NIR image through local Linear Mapping
2014 IEEE International Conference on Multimedia and Expo (ICME), 2014Co-Authors: Tao Yue, Mingting Sun, Zhengyou Zhang, Jinli Suo, Qionghai DaiAbstract:Image acquisition in a low light environment requires long exposure to achieve acceptable signal-to-noise ratio, which however causes blurry effect. This paper addresses this problem by using a sharp near-infrared (NIR) image when the environment has sufficient NIR light. We assume that an RGB and NIR image pair has a Linear Mapping in a local area and that the Mapping function is valid for both the blur and sharp image pairs. Using this property, we solve the sharp RGB images from a blurred RGB image and the corres ponding s harp NIR image. The effectiveness of the proposed algorithm is verified with both synthetic and real captured datasets.
Tao Yue - One of the best experts on this subject based on the ideXlab platform.
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deblur a blurred rgb image with a sharp nir image through local Linear Mapping
International Conference on Multimedia and Expo, 2014Co-Authors: Tao Yue, Mingting Sun, Zhengyou Zhang, Jinli Suo, Qionghai DaiAbstract:Image acquisition in a low light environment requires long exposure to achieve acceptable signal-to-noise ratio, which however causes blurry effect. This paper addresses this problem by using a sharp near-infrared (NIR) image when the environment has sufficient NIR light. We assume that an RGB and NIR image pair has a Linear Mapping in a local area and that the Mapping function is valid for both the blur and sharp image pairs. Using this property, we solve the sharp RGB images from a blurred RGB image and the corres ponding s harp NIR image. The effectiveness of the proposed algorithm is verified with both synthetic and real captured datasets.
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ICME - Deblur a blurred RGB image with a sharp NIR image through local Linear Mapping
2014 IEEE International Conference on Multimedia and Expo (ICME), 2014Co-Authors: Tao Yue, Mingting Sun, Zhengyou Zhang, Jinli Suo, Qionghai DaiAbstract:Image acquisition in a low light environment requires long exposure to achieve acceptable signal-to-noise ratio, which however causes blurry effect. This paper addresses this problem by using a sharp near-infrared (NIR) image when the environment has sufficient NIR light. We assume that an RGB and NIR image pair has a Linear Mapping in a local area and that the Mapping function is valid for both the blur and sharp image pairs. Using this property, we solve the sharp RGB images from a blurred RGB image and the corres ponding s harp NIR image. The effectiveness of the proposed algorithm is verified with both synthetic and real captured datasets.
Jinli Suo - One of the best experts on this subject based on the ideXlab platform.
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deblur a blurred rgb image with a sharp nir image through local Linear Mapping
International Conference on Multimedia and Expo, 2014Co-Authors: Tao Yue, Mingting Sun, Zhengyou Zhang, Jinli Suo, Qionghai DaiAbstract:Image acquisition in a low light environment requires long exposure to achieve acceptable signal-to-noise ratio, which however causes blurry effect. This paper addresses this problem by using a sharp near-infrared (NIR) image when the environment has sufficient NIR light. We assume that an RGB and NIR image pair has a Linear Mapping in a local area and that the Mapping function is valid for both the blur and sharp image pairs. Using this property, we solve the sharp RGB images from a blurred RGB image and the corres ponding s harp NIR image. The effectiveness of the proposed algorithm is verified with both synthetic and real captured datasets.
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ICME - Deblur a blurred RGB image with a sharp NIR image through local Linear Mapping
2014 IEEE International Conference on Multimedia and Expo (ICME), 2014Co-Authors: Tao Yue, Mingting Sun, Zhengyou Zhang, Jinli Suo, Qionghai DaiAbstract:Image acquisition in a low light environment requires long exposure to achieve acceptable signal-to-noise ratio, which however causes blurry effect. This paper addresses this problem by using a sharp near-infrared (NIR) image when the environment has sufficient NIR light. We assume that an RGB and NIR image pair has a Linear Mapping in a local area and that the Mapping function is valid for both the blur and sharp image pairs. Using this property, we solve the sharp RGB images from a blurred RGB image and the corres ponding s harp NIR image. The effectiveness of the proposed algorithm is verified with both synthetic and real captured datasets.
Mingting Sun - One of the best experts on this subject based on the ideXlab platform.
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deblur a blurred rgb image with a sharp nir image through local Linear Mapping
International Conference on Multimedia and Expo, 2014Co-Authors: Tao Yue, Mingting Sun, Zhengyou Zhang, Jinli Suo, Qionghai DaiAbstract:Image acquisition in a low light environment requires long exposure to achieve acceptable signal-to-noise ratio, which however causes blurry effect. This paper addresses this problem by using a sharp near-infrared (NIR) image when the environment has sufficient NIR light. We assume that an RGB and NIR image pair has a Linear Mapping in a local area and that the Mapping function is valid for both the blur and sharp image pairs. Using this property, we solve the sharp RGB images from a blurred RGB image and the corres ponding s harp NIR image. The effectiveness of the proposed algorithm is verified with both synthetic and real captured datasets.
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ICME - Deblur a blurred RGB image with a sharp NIR image through local Linear Mapping
2014 IEEE International Conference on Multimedia and Expo (ICME), 2014Co-Authors: Tao Yue, Mingting Sun, Zhengyou Zhang, Jinli Suo, Qionghai DaiAbstract:Image acquisition in a low light environment requires long exposure to achieve acceptable signal-to-noise ratio, which however causes blurry effect. This paper addresses this problem by using a sharp near-infrared (NIR) image when the environment has sufficient NIR light. We assume that an RGB and NIR image pair has a Linear Mapping in a local area and that the Mapping function is valid for both the blur and sharp image pairs. Using this property, we solve the sharp RGB images from a blurred RGB image and the corres ponding s harp NIR image. The effectiveness of the proposed algorithm is verified with both synthetic and real captured datasets.
Zhengyou Zhang - One of the best experts on this subject based on the ideXlab platform.
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deblur a blurred rgb image with a sharp nir image through local Linear Mapping
International Conference on Multimedia and Expo, 2014Co-Authors: Tao Yue, Mingting Sun, Zhengyou Zhang, Jinli Suo, Qionghai DaiAbstract:Image acquisition in a low light environment requires long exposure to achieve acceptable signal-to-noise ratio, which however causes blurry effect. This paper addresses this problem by using a sharp near-infrared (NIR) image when the environment has sufficient NIR light. We assume that an RGB and NIR image pair has a Linear Mapping in a local area and that the Mapping function is valid for both the blur and sharp image pairs. Using this property, we solve the sharp RGB images from a blurred RGB image and the corres ponding s harp NIR image. The effectiveness of the proposed algorithm is verified with both synthetic and real captured datasets.
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ICME - Deblur a blurred RGB image with a sharp NIR image through local Linear Mapping
2014 IEEE International Conference on Multimedia and Expo (ICME), 2014Co-Authors: Tao Yue, Mingting Sun, Zhengyou Zhang, Jinli Suo, Qionghai DaiAbstract:Image acquisition in a low light environment requires long exposure to achieve acceptable signal-to-noise ratio, which however causes blurry effect. This paper addresses this problem by using a sharp near-infrared (NIR) image when the environment has sufficient NIR light. We assume that an RGB and NIR image pair has a Linear Mapping in a local area and that the Mapping function is valid for both the blur and sharp image pairs. Using this property, we solve the sharp RGB images from a blurred RGB image and the corres ponding s harp NIR image. The effectiveness of the proposed algorithm is verified with both synthetic and real captured datasets.
