The Experts below are selected from a list of 14115 Experts worldwide ranked by ideXlab platform
Wenda Cao - One of the best experts on this subject based on the ideXlab platform.
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objective image quality assessment for high resolution photospheric images by Median Filter gradient similarity
arXiv: Instrumentation and Methods for Astrophysics, 2017Co-Authors: Hui Deng, Dandan Zhang, Tianyu Wang, Feng Wang, Zhong Liu, Yongyuan Xiang, Zhenyu Jin, Wenda CaoAbstract:All next generation ground-based and space-based solar telescopes require a good quality assessment metric in order to evaluate their imaging performance. In this paper, a new image quality metric, the Median Filter gradient similarity (MFGS) is proposed for photospheric images. MFGS is a no-reference/blind objective image quality metric (IQM) by a measurement result between 0 and 1 and has been performed on short-exposure photospheric images captured by the New Vacuum Solar Telescope (NVST) of the Fuxian Solar Observatory and by the Solar Optical Telescope (SOT) onboard the Hinode satellite, respectively. The results show that: (1)the measured value of MFGS changes monotonically from 1 to 0 with degradation of image quality; (2)there exists a linear correlation between the measured values of MFGS and root-mean-square-contrast (RMS-contrast) of granulation; (3)MFGS is less affected by the image contents than the granular RMS-contrast. Overall, MFGS is a good alternative for the quality assessment of photospheric images.
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objective image quality assessment for high resolution photospheric images by Median Filter gradient similarity
Solar Physics, 2015Co-Authors: Hui Deng, Dandan Zhang, Tianyu Wang, Feng Wang, Zhong Liu, Yongyuan Xiang, Zhenyu Jin, Wenda CaoAbstract:All next-generation ground-based and space-based solar telescopes require a good quality-assessment metric to evaluate their imaging performance. In this paper, a new image quality metric, the Median Filter-gradient similarity (MFGS) is proposed for photospheric images. MFGS is a no-reference/blind objective image-quality metric (IQM) by a measurement result between 0 and 1 and has been performed on short-exposure photospheric images captured by the New Vacuum Solar Telescope (NVST) of the Fuxian Solar Observatory and by the Solar Optical Telescope (SOT) onboard the Hinode satellite, respectively. The results show that (1) the measured value of the MFGS changes monotonically from 1 to 0 with degradation of image quality; (2) there exists a linear correlation between the measured values of the MFGS and the root-mean-square contrast (RMS-contrast) of the granulation; (3) the MFGS is less affected by the image contents than the granular RMS-contrast. Overall, the MFGS is a good alternative for the quality assessment of photospheric images.
Feng Wang - One of the best experts on this subject based on the ideXlab platform.
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objective image quality assessment for high resolution photospheric images by Median Filter gradient similarity
arXiv: Instrumentation and Methods for Astrophysics, 2017Co-Authors: Hui Deng, Dandan Zhang, Tianyu Wang, Feng Wang, Zhong Liu, Yongyuan Xiang, Zhenyu Jin, Wenda CaoAbstract:All next generation ground-based and space-based solar telescopes require a good quality assessment metric in order to evaluate their imaging performance. In this paper, a new image quality metric, the Median Filter gradient similarity (MFGS) is proposed for photospheric images. MFGS is a no-reference/blind objective image quality metric (IQM) by a measurement result between 0 and 1 and has been performed on short-exposure photospheric images captured by the New Vacuum Solar Telescope (NVST) of the Fuxian Solar Observatory and by the Solar Optical Telescope (SOT) onboard the Hinode satellite, respectively. The results show that: (1)the measured value of MFGS changes monotonically from 1 to 0 with degradation of image quality; (2)there exists a linear correlation between the measured values of MFGS and root-mean-square-contrast (RMS-contrast) of granulation; (3)MFGS is less affected by the image contents than the granular RMS-contrast. Overall, MFGS is a good alternative for the quality assessment of photospheric images.
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objective image quality assessment for high resolution photospheric images by Median Filter gradient similarity
Solar Physics, 2015Co-Authors: Hui Deng, Dandan Zhang, Tianyu Wang, Feng Wang, Zhong Liu, Yongyuan Xiang, Zhenyu Jin, Wenda CaoAbstract:All next-generation ground-based and space-based solar telescopes require a good quality-assessment metric to evaluate their imaging performance. In this paper, a new image quality metric, the Median Filter-gradient similarity (MFGS) is proposed for photospheric images. MFGS is a no-reference/blind objective image-quality metric (IQM) by a measurement result between 0 and 1 and has been performed on short-exposure photospheric images captured by the New Vacuum Solar Telescope (NVST) of the Fuxian Solar Observatory and by the Solar Optical Telescope (SOT) onboard the Hinode satellite, respectively. The results show that (1) the measured value of the MFGS changes monotonically from 1 to 0 with degradation of image quality; (2) there exists a linear correlation between the measured values of the MFGS and the root-mean-square contrast (RMS-contrast) of the granulation; (3) the MFGS is less affected by the image contents than the granular RMS-contrast. Overall, the MFGS is a good alternative for the quality assessment of photospheric images.
Zhaoxiang Zang - One of the best experts on this subject based on the ideXlab platform.
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modified switching Median Filter for impulse noise removal
Signal Processing, 2010Co-Authors: Gaihua Wang, Weimin Pan, Zhaoxiang ZangAbstract:In this paper, a modified switching Median Filter is presented for noise reduction in color images that are corrupted with impulse (salt and pepper) noise. It is a two-phase noise detector: in the first phase, we use the adaptive vector Median Filter detection method to identify pixels that are likely to have been corrupted by noise (as noise candidates); in the second phase, these noise candidates are judged by using four one-dimensional Laplacian operators, which allow edge pixels to be preserved. Extensive experiments show that the proposed method outperforms many existing vector Filters in terms of Filtering performance. In particular, the proposed approach can effectively preserve thin lines, fine details, and image edges.
Hui Deng - One of the best experts on this subject based on the ideXlab platform.
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objective image quality assessment for high resolution photospheric images by Median Filter gradient similarity
arXiv: Instrumentation and Methods for Astrophysics, 2017Co-Authors: Hui Deng, Dandan Zhang, Tianyu Wang, Feng Wang, Zhong Liu, Yongyuan Xiang, Zhenyu Jin, Wenda CaoAbstract:All next generation ground-based and space-based solar telescopes require a good quality assessment metric in order to evaluate their imaging performance. In this paper, a new image quality metric, the Median Filter gradient similarity (MFGS) is proposed for photospheric images. MFGS is a no-reference/blind objective image quality metric (IQM) by a measurement result between 0 and 1 and has been performed on short-exposure photospheric images captured by the New Vacuum Solar Telescope (NVST) of the Fuxian Solar Observatory and by the Solar Optical Telescope (SOT) onboard the Hinode satellite, respectively. The results show that: (1)the measured value of MFGS changes monotonically from 1 to 0 with degradation of image quality; (2)there exists a linear correlation between the measured values of MFGS and root-mean-square-contrast (RMS-contrast) of granulation; (3)MFGS is less affected by the image contents than the granular RMS-contrast. Overall, MFGS is a good alternative for the quality assessment of photospheric images.
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objective image quality assessment for high resolution photospheric images by Median Filter gradient similarity
Solar Physics, 2015Co-Authors: Hui Deng, Dandan Zhang, Tianyu Wang, Feng Wang, Zhong Liu, Yongyuan Xiang, Zhenyu Jin, Wenda CaoAbstract:All next-generation ground-based and space-based solar telescopes require a good quality-assessment metric to evaluate their imaging performance. In this paper, a new image quality metric, the Median Filter-gradient similarity (MFGS) is proposed for photospheric images. MFGS is a no-reference/blind objective image-quality metric (IQM) by a measurement result between 0 and 1 and has been performed on short-exposure photospheric images captured by the New Vacuum Solar Telescope (NVST) of the Fuxian Solar Observatory and by the Solar Optical Telescope (SOT) onboard the Hinode satellite, respectively. The results show that (1) the measured value of the MFGS changes monotonically from 1 to 0 with degradation of image quality; (2) there exists a linear correlation between the measured values of the MFGS and the root-mean-square contrast (RMS-contrast) of the granulation; (3) the MFGS is less affected by the image contents than the granular RMS-contrast. Overall, the MFGS is a good alternative for the quality assessment of photospheric images.
Paota Yu - One of the best experts on this subject based on the ideXlab platform.
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partition fuzzy Median Filter based on fuzzy rules for image restoration
Fuzzy Sets and Systems, 2004Co-Authors: Paota YuAbstract:In this paper, a novel adaptive Median-based Filter, called the partition fuzzy Median (PFM) Filter, is proposed for improving the Median-based Filter to preserve image details while effectively suppressing impulsive noises. The proposed Filter achieves its effect through a summation of the weighted output of the Median Filter and the related weighted input signal. The weights are set in accordance with the fuzzy rules. In order to design this weight function, a method to partition of the observation vector space and a learning approach are proposed so that the mean square error of the Filter output can be minimum. Based on the constrained least mean square algorithm, an iterative learning procedure is derived and its convergence property is investigated. As for the noise suppressing on both fixed- and random-valued impulses without degrading the quality of fine details, extensive experimental results demonstrate that the proposed Filter outperforms the other Median-based Filters in the literature. The new Filter also provides excellent robustness with respect to various percentages of impulse noise in our testing examples.
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adaptive two pass Median Filter based on support vector machines for image restoration
Neural Computation, 2004Co-Authors: Paota YuAbstract:In this letter, a novel adaptive Filter, the adaptive two-pass Median (ATM) Filter based on support vector machines (SVMs), is proposed to preserve more image details while effectively suppressing impulse noise for image restoration. The proposed Filter is composed of a noise decision maker and two-pass Median Filters. Our new approach basically uses an SVM impulse detector to judge whether the input pixel is noise. If a pixel is detected as a corrupted pixel, the noise-free reduction Median Filter will be triggered to replace it. Otherwise, it remains unchanged. Then, to improve the quality of the restored image, a decision impulse Filter is put to work in the second-pass Filtering procedure. As for the noise suppressing both fixed-valued and random-valued impulses without degrading the quality of the fine details, the results of our extensive experiments demonstrate that the proposed Filter outperforms earlier Median-based Filters in the literature. Our new Filter also provides excellent robustness at various percentages of impulse noise.
