In order to alleviate the shortcomings of most blind deconvolution algorithms,this paper proposes an improved fast algorithm for blind deconvolution based on decorrelation technique and broadband block matrix.Althougt...In order to alleviate the shortcomings of most blind deconvolution algorithms,this paper proposes an improved fast algorithm for blind deconvolution based on decorrelation technique and broadband block matrix.Althougth the original algorithm can overcome the shortcomings of current blind deconvolution algorithms,it has a constraint that the number of the source signals must be less than that of the channels.The improved algorithm deletes this constraint by using decorrelation technique.Besides,the improved algorithm raises the separation speed in terms of improving the computing methods of the output signal matrix.Simulation results demonstrate the validation and fast separation of the improved algorithm.展开更多
This paper presents a new blind XPIC and a new adaptive blind deconvolutional algorithm based on HOS processing, which separates and equalizes the signals in real time. The simulation results demonstrate that the perf...This paper presents a new blind XPIC and a new adaptive blind deconvolutional algorithm based on HOS processing, which separates and equalizes the signals in real time. The simulation results demonstrate that the performance of the proposed adaptive blind algorithm,compared with the conventional algorithms, is outstanding with the feature of feasibility, stability and fast convergence rate.展开更多
In[3],Chan and Wong proposed to use total variational regularization for both images and point spread functions in blind deconvolution.Their experimental results show that the detail of the restored images cannot be r...In[3],Chan and Wong proposed to use total variational regularization for both images and point spread functions in blind deconvolution.Their experimental results show that the detail of the restored images cannot be recovered.In this paper,we consider images in Lipschitz spaces,and propose to use Lipschitz regularization for images and total variational regularization for point spread functions in blind deconvolution.Our experimental results show that such combination of Lipschitz and total variational regularization methods can recover both images and point spread functions quite well.展开更多
提出了一种基于加速正则化Richardson-Lucy(RL)算法的大气湍流退化图像盲复原方法(AccRLTV-IBD)。在总变分(TV)正则化RL算法的基础上,引入二阶矢量外推加速技术对其进行加速,形成加速正则化RL(AccRLTV)算法,并将该算法应用到迭代盲目反...提出了一种基于加速正则化Richardson-Lucy(RL)算法的大气湍流退化图像盲复原方法(AccRLTV-IBD)。在总变分(TV)正则化RL算法的基础上,引入二阶矢量外推加速技术对其进行加速,形成加速正则化RL(AccRLTV)算法,并将该算法应用到迭代盲目反卷积(IBD)算法中。使用长曝光大气湍流光学传递函数(OTF)的物理模型或根据图像来获取初始的点扩散函数(PSF),在灰度平均梯度(gray mean grads,GMG)的基础上定义了一个相对灰度平均梯度(relative gray mean grads,RGMG)参数作为无参考图像复原质量的评价标准.模拟图像和实际湍流退化图像复原结果表明,基于RL的IBD算法要优于基于Wiener滤波的IBD算法,并且与RL-IBD算法相比,AccRLTV-IBD收敛速度更快,复原效果更好。展开更多
基金Natural Science Fund of Anhui Province of China (050420101)
文摘In order to alleviate the shortcomings of most blind deconvolution algorithms,this paper proposes an improved fast algorithm for blind deconvolution based on decorrelation technique and broadband block matrix.Althougth the original algorithm can overcome the shortcomings of current blind deconvolution algorithms,it has a constraint that the number of the source signals must be less than that of the channels.The improved algorithm deletes this constraint by using decorrelation technique.Besides,the improved algorithm raises the separation speed in terms of improving the computing methods of the output signal matrix.Simulation results demonstrate the validation and fast separation of the improved algorithm.
文摘This paper presents a new blind XPIC and a new adaptive blind deconvolutional algorithm based on HOS processing, which separates and equalizes the signals in real time. The simulation results demonstrate that the performance of the proposed adaptive blind algorithm,compared with the conventional algorithms, is outstanding with the feature of feasibility, stability and fast convergence rate.
基金This research is supported in part by RGC 7046/03P,7035/04P,7035/05P and HKBU FRGs.
文摘In[3],Chan and Wong proposed to use total variational regularization for both images and point spread functions in blind deconvolution.Their experimental results show that the detail of the restored images cannot be recovered.In this paper,we consider images in Lipschitz spaces,and propose to use Lipschitz regularization for images and total variational regularization for point spread functions in blind deconvolution.Our experimental results show that such combination of Lipschitz and total variational regularization methods can recover both images and point spread functions quite well.
文摘提出了一种基于加速正则化Richardson-Lucy(RL)算法的大气湍流退化图像盲复原方法(AccRLTV-IBD)。在总变分(TV)正则化RL算法的基础上,引入二阶矢量外推加速技术对其进行加速,形成加速正则化RL(AccRLTV)算法,并将该算法应用到迭代盲目反卷积(IBD)算法中。使用长曝光大气湍流光学传递函数(OTF)的物理模型或根据图像来获取初始的点扩散函数(PSF),在灰度平均梯度(gray mean grads,GMG)的基础上定义了一个相对灰度平均梯度(relative gray mean grads,RGMG)参数作为无参考图像复原质量的评价标准.模拟图像和实际湍流退化图像复原结果表明,基于RL的IBD算法要优于基于Wiener滤波的IBD算法,并且与RL-IBD算法相比,AccRLTV-IBD收敛速度更快,复原效果更好。
