图像序列超分辨率处理中充分帧数的估计

充分帧数（SNL）估计是图像序列超分辨率技术走向实际应用的关键问题。本文首次提出了适合实际应用的SNL估计方法从采集到的低分辨率图像序列中选取不同长度（帧数）的子图像序列参与超分辨率处理,得到一个结果图像序列;测量结果图像序列中图像间的差异;通过分析差异曲线估计出SNL。实际数据证明,本文的方法能够准确、稳定地估计出SNL,为图像序列超分辨率技术的工程应用提供有效的支持。

Estimating the Sufficient Number of Low-Resolution Images for Super-Resolution Processing

Sufficient Number of Low-resolution Images (SNL) estimation is a key problem in the application of super-resolution (SR) in image sequences. This paper presents a practical SNL estimation algorithm. The basic idea is to utilize the convergence of the reconstructed high-resolution images (HRI) considering the increase of SNL. First,the sub-sequences with different numbers of frames are put into the SR procedure. Each sub-sequence corresponds to a HRI, so we have a sequence of HRIs. Second, the differences between the HRIs are measured. Finally, SNL is estimated though the analyses of the difference curve of the HRIs. The experiments on real data demonstrate that the proposed algorithm estimates the SNL accurately and stably. The presented method can be used to support the practical application of the SR technology.