基于投影网络的遥感影像超分辨率重建方法

针对遥感影像数据量大、地形起伏大、覆盖范围 广的特点,本文提出了一种基于卷积神经网络的遥感影像超分辨重建 方法,该方法联合密集网络和深度反投影网络,组成了密集投影单元,形成深度密集投影网 络,解决了传统算法在遥感影像超分 辨率重建中存在的纹理表征不够,细节提取不足、训练困难等问题。实验结果表明,在多个 遥感影像数据集上,本文与其他对比 方法相比,PSNR和SSIM有明显提升,重建出的遥感影像纹理标征和细节特征更加丰富。

Super-resolution reconstruction method of remote sensing image based on project ion network

Aiming at the characteristics of large amount of remote sensing image data,large terrain fluctuations and wide coverage,this paper proposes a method for super-resolution reconstruction of remote sensing i mage based on convolutional neural network.This method combines dense network and deep back projection network to form dense projection .The unit forms a deep dense projection network, which solves the problems of insufficient texture representation,insufficient d etail extraction,and difficult training in traditional algorithms in the super-resolution reconstruction of remote sensing images.The experiment al results show that on multiple remote sensing image data sets,compared with other comparison methods,the PSNR and SSIM are significantl y improved,and the reconstructed remote sensing image texture signs and details are more abundant.