The goal of Super-resolution restoration is to draw a high-resolution image from a low-resolution ratio image array.
图像超分辨率复原的目的是从一个低分辨率图像序列中提取一幅高分辨率图像。
Image super-resolution restoration and enhancement (SR) based on reconstruction is a typically ill-posed and high-dimensional problem, which needs effective regularization to stable the solution.
基于重建的超分辨率（SR）方法中，图像求解是典型的高维病态问题，需借助有效的正则来稳定求解。
A method of super resolution image restoration based on separation was proposed and the algorithm of adnate template was introduced.
提出了一种用于超分辨率复原的分离方法，并引入了级联模板算法。
In this paper we propose a blind super-resolution image restoration algorithm based on Support Vector Machines (SVM).
本文提出了一种基于支撑向量机的盲超分辨率图像复原算法。
In this paper we propose a blind super-resolution image restoration algorithm based on Support Vector Machines (SVM).
本文提出了一种基于支撑向量机的盲超分辨率图像复原算法。
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