Super - resolution ( sr ) image fusion is the technology of reconstructing a frame of image with high resolution from a group of warped , blurred and noised low - resolution ( lr ) images or video sequence about the same scene 超分辨率图像融合就是利用同一场景的多帧有相互位移的降质图像或视频序列来重建一帧高分辨率图像的技术。
Technology of super - resolution has been widely used in remote sensing military surveillance and medical diagnosis , etc . the method of super - resolution image reconstruction based on wavelet is considered in this paper 超分辨技术已经在卫星遥感、军事侦察、医学诊断等很多方面取得了广泛应用。本文主要研究了基于小波的超分辨率图像重建方法。
Now , the research of super - resolution reconstruction technique basing on the image sequence focuses on two factors : ( d capturing an image sequence with slight displacement ; ? he reconstruction algorithm of high - resolution image 基于序列图像重构的超分辨率成像技术研究主要集中在两个方面：空间上互有位移的序列初始图像的获取；高分辨率图像的重构算法。
We can get higher resolution from two ways , one is improving hardware , the other is processing image in software . amelioration of hardware is costly , so super resolution is observing after its appearance 由于从硬件方面提高图像分辨率的代价十分高昂,因此,依靠算法软件实现超分辨率的技术一出现,就受到了极大的关注,现在,其研究成果已被广泛应用于各个领域。
So far , the technology of super - resolution image fusion has been extensively applied to remote sensing , military , public security , computer vision , medical imaging , multi - media electronic consuming , image compression and so on 目前,图像超分辨率融合技术已经在遥感、军事、公共安全、计算机视觉、医学成像、多媒体电子消费、图像压缩等领域得到了广泛应用。
Therefore , this technology has great prospect with significant applicational value . this thesis firstly introduces the developmental process of super - resolution image fusion as well as all kinds of algorithms basing on both frequency domain and spatial domain 本文首先对超分辨率图像融合的发展历程和超分辨率图像融合的频域及空域的各种算法进行了介绍,并分析和比较了各种算法的优缺点。
This paper covers the investigation of super - resolution reconstruction problem in medical image processing , and the implementing of registration and super - resolution reconstruction from flourescein angiograms of retinal blood flow as sampled data are discussed 摘要主要研究在医学图像处理中超分辨率图像的重建问题，并以视网膜血管造影图像序列为采样数据，完成对其配准与超分辨率重建的处理过程。
Recent years have seen growing interest in studying of super - resolution image reconstruction technology , which refers to image processing algorithms to reconstruct high quality and high - resolution ( hr ) images from a sequence of degraded low - resolution ( lr ) images 近年来,越来越多的研究者对超分辨率图像重建技术充满兴趣,所谓图像超分辨处理就是从一序列降质的低分辨率图像中获取高分辨率高质量的图像。
Finally , we use a iterative method to interpolated reconstruct the high resolution images . we apply our method in the superresolution reconstruction process . the numeric results and the distinct reconstructed images prove the feasible of our method 最后，做为计算实例，在本文的第五章中，把我们提出的方法应用于超分辨率图象重建过程中，得到了很好的数值结果和清晰的重建图象，证明了该方法的有效性。
The major work implemented in this dissertation is presented as follows : 1 . give a brief introduction of the rgistration method based on the elementary segments of differetial rectification and the motion model estimate with conjugate gradient . 2 接着讨论了如何具体实现超分辨率重建问题，本文主要做了以下工作： 1 、简要介绍了基于小面元微分纠正的配准方法和一种基于共轭梯度的运动模型估计方法，这是超分辨率影像重建的基础。
