由于微透镜影像分割了原始全光影像,无法应用全局优化算法,而采用WTA(winner-take-all)算法得到的深度影像虽然连续,但包含错误估计的深度信息;利用全局优化计算得到的深度图可以消除错误估计的深度信息,但是受到代价计算时深度离散化...由于微透镜影像分割了原始全光影像,无法应用全局优化算法,而采用WTA(winner-take-all)算法得到的深度影像虽然连续,但包含错误估计的深度信息;利用全局优化计算得到的深度图可以消除错误估计的深度信息,但是受到代价计算时深度离散化的限制而不连续。基于上述情况,提出一种直接处理微透镜阵列全光影像的代价投影策略,在投影图像上构建代价立方体(cost volume,CV),同时采用MRFsP(Markov Random Fields Propagation)进行优化,结合WTA方法的优势改善离散深度图像。实验结果表明,与现有方法对比,利用MRFsP优化后的深度图既能消除错误匹配点,也能保持连续。展开更多
Abstract We use moderate deviations to study the signal detection problem for a diffusion model. We establish a moderate deviation principle for the log-likelihood function of the diffusion model. Then applying the mo...Abstract We use moderate deviations to study the signal detection problem for a diffusion model. We establish a moderate deviation principle for the log-likelihood function of the diffusion model. Then applying the moderate deviation estimates to hypothesis testing for signal detection problem we give a decision region such that its error probability of the second kind tends to zero with faster speed than the error probability of the first kind when the error probability of the first kind is approximated by e-ατ（T）, where α〉 0, τ（T） = o（T） and τ（T）→∞ as the observation time T goes to infinity.展开更多
文摘由于微透镜影像分割了原始全光影像,无法应用全局优化算法,而采用WTA(winner-take-all)算法得到的深度影像虽然连续,但包含错误估计的深度信息;利用全局优化计算得到的深度图可以消除错误估计的深度信息,但是受到代价计算时深度离散化的限制而不连续。基于上述情况,提出一种直接处理微透镜阵列全光影像的代价投影策略,在投影图像上构建代价立方体(cost volume,CV),同时采用MRFsP(Markov Random Fields Propagation)进行优化,结合WTA方法的优势改善离散深度图像。实验结果表明,与现有方法对比,利用MRFsP优化后的深度图既能消除错误匹配点,也能保持连续。
基金supported by National Natural Science Foundation of China (Grant Nos.10871153 and 11171262)the Specialized Research Fund for the Doctoral Program of Higher Education of China (Grant No. 200804860048)
文摘Abstract We use moderate deviations to study the signal detection problem for a diffusion model. We establish a moderate deviation principle for the log-likelihood function of the diffusion model. Then applying the moderate deviation estimates to hypothesis testing for signal detection problem we give a decision region such that its error probability of the second kind tends to zero with faster speed than the error probability of the first kind when the error probability of the first kind is approximated by e-ατ（T）, where α〉 0, τ（T） = o（T） and τ（T）→∞ as the observation time T goes to infinity.
