In order to enhance the image contrast and quality, inspired by the interesting observation that an increase in noise intensity tends to narrow the dynamic range of the local standard deviation (LSD) of an image, a tr...In order to enhance the image contrast and quality, inspired by the interesting observation that an increase in noise intensity tends to narrow the dynamic range of the local standard deviation (LSD) of an image, a tree-structured group sparse optimization model in the wavelet domain is proposed for image denoising. The compressed dynamic range of LSD caused by noise leads to a contrast reduction in the image, as well as the degradation of image quality. To equalize the LSD distribution, sparsity on the LSD matrix is enforced by employing a mixed norm as a regularizer in the image denoising model. This mixed norm introduces a coupling between wavelet coefficients and provides a tree-structured group scheme. The alternating direction method of multipliers (ADMM) and the fast iterative shrinkage-thresholding algorithm (FISTA) are applied to solve the group sparse model based on different cases. Several experiments are conducted to verify the effectiveness of the proposed model. The experimental results indicate that the proposed group sparse model can efficiently equalize the LSD distribution and therefore can improve the image contrast and quality.展开更多
Group sparse residual constraint with non-local priors(GSRC)has achieved great success in image restoration producing stateof-the-art performance.In the GSRC model,the l_(1)norm minimization is employed to reduce the ...Group sparse residual constraint with non-local priors(GSRC)has achieved great success in image restoration producing stateof-the-art performance.In the GSRC model,the l_(1)norm minimization is employed to reduce the group sparse residual.In recent years,nonconvex regularization terms have been widely used in image denoising problems,which have achieved better results in denoising than convex regularization terms.In this paper,we use the ratio of the l_(1)and l_(2)norm instead of the l_(1)norm to propose a new image denoising model,i.e.,a group sparse residual constraint model with l_(1)/l_(2)minimization(GSRC-l_(1)/l_(2)).Due to the computational difficulties arisen from the non-convexity and non-linearity,we focus on a constrained optimization problem that can be solved by alternative direction method of multipliers(ADMM).Experimental results of image denoising show that the pro-posed model outperforms several state-of-the-art image denoising methods both visually and quantitatively.展开更多
The spontaneous emission of an excited atom embedded in photonic crystals with two atomic position-dependent bands is investigated.The distribution of the density of states between two bands depends on the atomic posi...The spontaneous emission of an excited atom embedded in photonic crystals with two atomic position-dependent bands is investigated.The distribution of the density of states between two bands depends on the atomic position in a unit cell of the photonic crystal and is described with an atomic position-dependent parameter.The result shows that the emitted field and the time evolution of the upper-level population are affected by the atomic position and the gap width.The spontaneous emission spectrum in free space can be shifted and narrowed with the photonic reservoir and the gap width.展开更多
基金The National Natural Science Foundation of China(No.61701004,11504003)the Natural Science Foundation of Anhui Province(No.1708085QA15)
文摘In order to enhance the image contrast and quality, inspired by the interesting observation that an increase in noise intensity tends to narrow the dynamic range of the local standard deviation (LSD) of an image, a tree-structured group sparse optimization model in the wavelet domain is proposed for image denoising. The compressed dynamic range of LSD caused by noise leads to a contrast reduction in the image, as well as the degradation of image quality. To equalize the LSD distribution, sparsity on the LSD matrix is enforced by employing a mixed norm as a regularizer in the image denoising model. This mixed norm introduces a coupling between wavelet coefficients and provides a tree-structured group scheme. The alternating direction method of multipliers (ADMM) and the fast iterative shrinkage-thresholding algorithm (FISTA) are applied to solve the group sparse model based on different cases. Several experiments are conducted to verify the effectiveness of the proposed model. The experimental results indicate that the proposed group sparse model can efficiently equalize the LSD distribution and therefore can improve the image contrast and quality.
基金Supported by the Open Fund of Key Laboratory of Anhui Higher Education Institutes(CS2021-07)the National Natural Science Foundation of China(61701004),the Outstanding Young Talents Support Program of Anhui Province(GXYQ 2021178)University Natural Science Research Project of Anhui Province of China(KJ2020A0238)。
文摘Group sparse residual constraint with non-local priors(GSRC)has achieved great success in image restoration producing stateof-the-art performance.In the GSRC model,the l_(1)norm minimization is employed to reduce the group sparse residual.In recent years,nonconvex regularization terms have been widely used in image denoising problems,which have achieved better results in denoising than convex regularization terms.In this paper,we use the ratio of the l_(1)and l_(2)norm instead of the l_(1)norm to propose a new image denoising model,i.e.,a group sparse residual constraint model with l_(1)/l_(2)minimization(GSRC-l_(1)/l_(2)).Due to the computational difficulties arisen from the non-convexity and non-linearity,we focus on a constrained optimization problem that can be solved by alternative direction method of multipliers(ADMM).Experimental results of image denoising show that the pro-posed model outperforms several state-of-the-art image denoising methods both visually and quantitatively.
基金supported by the Natural Science College Key Projects of Anhui Province (Grant Nos. KJ2010A335 and KJ2012Z023)the National Natural Science Foundation of China (Grant Nos. 41075027 and 61205115)the Key Project of Chinese Ministry of Education (Grant No. 212076)
文摘The spontaneous emission of an excited atom embedded in photonic crystals with two atomic position-dependent bands is investigated.The distribution of the density of states between two bands depends on the atomic position in a unit cell of the photonic crystal and is described with an atomic position-dependent parameter.The result shows that the emitted field and the time evolution of the upper-level population are affected by the atomic position and the gap width.The spontaneous emission spectrum in free space can be shifted and narrowed with the photonic reservoir and the gap width.
