A new method of super-resolution image reconstruction is proposed, which uses a three-step-training error backpropagation neural network （BPNN） to realize the super-resolution reconstruction （SRR） of satellite ima...A new method of super-resolution image reconstruction is proposed, which uses a three-step-training error backpropagation neural network （BPNN） to realize the super-resolution reconstruction （SRR） of satellite image. The method is based on BPNN. First, three groups learning samples with different resolutions are obtained according to image observation model, and then vector mappings are respectively used to those three group learning samples to speed up the convergence of BPNN, at last, three times consecutive training are carried on the BPNN. Training samples used in each step are of higher resolution than those used in the previous steps, so the increasing weights store a great amount of information for SRR, and network performance and generalization ability are improved greatly. Simulation and generalization tests are carried on the well-trained three-step-training NN respectively, and the reconstruction results with higher resolution images verify the effectiveness and validity of this method.展开更多
本文论证了超分辨率图像复原计算中的两个性质,并基于此在MAP(Maximum A Posteriori)框架下提出了一种新的纹理自适应算法.算法首先根据低分辨率图像和高分辨率图像近似计算的可类比性质计算初始图像,使初始图像的质量更高,并根据超分...本文论证了超分辨率图像复原计算中的两个性质,并基于此在MAP(Maximum A Posteriori)框架下提出了一种新的纹理自适应算法.算法首先根据低分辨率图像和高分辨率图像近似计算的可类比性质计算初始图像,使初始图像的质量更高,并根据超分辨率复原图像阶跃边缘的陡坡性质,将三边滤波正则化应用于迭代运算中,更好地保护了图像的陡坡和屋顶边缘.算法可根据图像的纹理自动计算初始图像融合参数以及正则化函数中的梯度阈值等参数,解决了以往超分辨率图像复原算法参数调整复杂的问题.实验结果表明,本文算法在没有人工参与的情况下,重建图像的客观评价和主观质量均有明显提高.展开更多
提出一种预估计混叠度的PEMAP(pre-estimated MAP (maximum a posteriori))算法,用于卫星图像的地面超分辨率处理.它通过频域分析确定卫星图像的混叠度,将其作为先验信息在空域控制MAP估计的循环迭代,联合估计帧间位移和高分辨率图像....提出一种预估计混叠度的PEMAP(pre-estimated MAP (maximum a posteriori))算法,用于卫星图像的地面超分辨率处理.它通过频域分析确定卫星图像的混叠度,将其作为先验信息在空域控制MAP估计的循环迭代,联合估计帧间位移和高分辨率图像.该算法克服了最大后验概率MAP算法的盲目性和不稳定性,使其适应性更好.实际的卫星图像处理显示了较好的处理效果.展开更多
超分辨率重建在视频监控、高清晰度电视、遥感图像、医学图像处理等领域具有广阔的应用前景.最大后验估计(maximum a posteriori,MAP)法是普遍采用的一种超分辨率重建方法.针对传统MAP法存在的局限性,本文提出了一种基于MAP框架的时空...超分辨率重建在视频监控、高清晰度电视、遥感图像、医学图像处理等领域具有广阔的应用前景.最大后验估计(maximum a posteriori,MAP)法是普遍采用的一种超分辨率重建方法.针对传统MAP法存在的局限性,本文提出了一种基于MAP框架的时空联合自适应视频序列超分辨率重建算法.时空联合自适应机制的引入使得算法在保持边缘的同时可减小错误运动估计矢量对重建图像质量的影响.实验结果表明,算法具有重建质量好、边缘保持能力强、收敛速度快等特点.展开更多
文摘A new method of super-resolution image reconstruction is proposed, which uses a three-step-training error backpropagation neural network （BPNN） to realize the super-resolution reconstruction （SRR） of satellite image. The method is based on BPNN. First, three groups learning samples with different resolutions are obtained according to image observation model, and then vector mappings are respectively used to those three group learning samples to speed up the convergence of BPNN, at last, three times consecutive training are carried on the BPNN. Training samples used in each step are of higher resolution than those used in the previous steps, so the increasing weights store a great amount of information for SRR, and network performance and generalization ability are improved greatly. Simulation and generalization tests are carried on the well-trained three-step-training NN respectively, and the reconstruction results with higher resolution images verify the effectiveness and validity of this method.
文摘本文论证了超分辨率图像复原计算中的两个性质,并基于此在MAP(Maximum A Posteriori)框架下提出了一种新的纹理自适应算法.算法首先根据低分辨率图像和高分辨率图像近似计算的可类比性质计算初始图像,使初始图像的质量更高,并根据超分辨率复原图像阶跃边缘的陡坡性质,将三边滤波正则化应用于迭代运算中,更好地保护了图像的陡坡和屋顶边缘.算法可根据图像的纹理自动计算初始图像融合参数以及正则化函数中的梯度阈值等参数,解决了以往超分辨率图像复原算法参数调整复杂的问题.实验结果表明,本文算法在没有人工参与的情况下,重建图像的客观评价和主观质量均有明显提高.
文摘提出一种预估计混叠度的PEMAP(pre-estimated MAP (maximum a posteriori))算法,用于卫星图像的地面超分辨率处理.它通过频域分析确定卫星图像的混叠度,将其作为先验信息在空域控制MAP估计的循环迭代,联合估计帧间位移和高分辨率图像.该算法克服了最大后验概率MAP算法的盲目性和不稳定性,使其适应性更好.实际的卫星图像处理显示了较好的处理效果.
文摘超分辨率重建在视频监控、高清晰度电视、遥感图像、医学图像处理等领域具有广阔的应用前景.最大后验估计(maximum a posteriori,MAP)法是普遍采用的一种超分辨率重建方法.针对传统MAP法存在的局限性,本文提出了一种基于MAP框架的时空联合自适应视频序列超分辨率重建算法.时空联合自适应机制的引入使得算法在保持边缘的同时可减小错误运动估计矢量对重建图像质量的影响.实验结果表明,算法具有重建质量好、边缘保持能力强、收敛速度快等特点.
