摘要
介绍了一种由多幅欠采样低分辨率图像重建一幅高分辨率图像的凸集投影超分辨率重建技术。首先介绍了超分辨率空间域迭代重建方法中一个至关重要的因素——成像过程模型;其次通过介绍凸集投影的理论依据,给出了插值—模拟采样迭代超分辨率重建方法的模型和重建步骤;最后通过实验数据对算法进行了验证。
Spatial resolution of image is a critical index of image quality, and also is an important parameter in the area of image application. However, there are many factors which can lower and degenerate the quality of images in the process of capturing images. An effective solution to this problem is the super-resolution image reconstruction, that means reconstructing a high resolution (HR) image from some low resolution (LR) images, and eliminating the additive noise and blur which is caused by the size of the detector and optical at the same time. In this paper,one of project of convex set method for reconstructing a super-resolution image from multiframe undersampling images is introduced.First,a very important factor-the model of the process of imaging in spatial domain iterative method for super-resolution image reconstruction is mentioned. Next the reconstruction model and its steps are introduced through introducing the theory of project of convex set method. At last, the technique is available by experiments. The result indicates the project of convex set method for super-resolution image reconstruction has preferable effect on multiframe undersampling remote sensing images, and the technique of super-resolution image reconstruction can used in lots of fields such as remote sensing, computer vision, public security, physic imaging and so on.
出处
《遥感技术与应用》
CSCD
2005年第3期361-365,共5页
Remote Sensing Technology and Application
关键词
欠采样
超分辨率图像重建
空间分辨率
凸集投影
插值—模拟采样迭代
Undersampling, Super-resolution image reconstruction, Spatial resolution, Project of convex set, Spatial iterative interpolation and simulated sampling
