Intensity-Based Image Registration and 3-D Image Denoising

本课题主要研究两个重要的图像分析问题。一个是关于图像配准，这是为了结构定位、差异检测和其他目的而匹配图像或图像体积。它广泛应用于医学成像、遥感、指纹或人脸识别等领域。第二个重点是在保留边缘和主要边缘特征的情况下对三维图像进行去噪。由于图像采集技术的快速发展，三维图像在磁共振成像(MRI)、功能磁共振成像(FMRI)等领域得到了越来越广泛的应用。然而，由于硬件不完善等原因，观测到的三维图像往往含有噪声，应该事先去除这些噪声，以便后续的图像分析更加可靠。在文献中，现有的图像配准方法大致可以分为两类：基于特征的图像配准方法和基于灰度的图像配准方法。由于特征选择通常是一个耗时和具有挑战性的过程，基于强度的IR方法在各种应用中变得流行起来。然而，现有的大多数基于灰度的红外方法都需要一个参数模型来描述图像匹配变换，这在实际应用中往往难以验证。在这个项目中，研究人员和他的同事们提出了一种基于强度的IR过程，而不会在匹配变换上强加任何参数形式。因此，该方法有可能极大地改进基于强度的红外技术，并极大地拓宽其应用范围。在文献中，现有的图像去噪方法大多是针对二维图像进行分析的。它们通常具有一定的能力来保留边的平面部分，但不能很好地保留边的角部分。它们对3-D情况的直接扩展通常不能有效地处理3-D图像，因为3-D图像的结构通常比2-D图像的结构复杂得多。本课题提出了一种新颖的三维图像去噪方法，能够很好地保留图像的边缘和主要边缘特征。因此，它将为三维图像去噪提供可靠的工具。从CT、MRI等医学成像技术的医学诊断到全球环境变化的卫星监测，图像在我们的社会中无处不在。该项目旨在改进图像配准和三维图像去噪技术，这些技术在各种成像应用中得到了广泛的应用。因此，它将通过它对改进医疗诊断、涉及指纹和人脸识别的安全系统、遥感技术等的直接影响，对我们的社会产生更广泛的影响。该项目还旨在通过其教育活动促进科学和工程人力资源的发展。例如，调查员开设了图像分析高级专题课程，各部门的研究生可以从中接受系统的科学研究培训。几名研究生正在和这位图像处理研究员一起做论文研究。研究人员和他的研究生开发的一些计算机软件包将发布在项目网页上，供其他研究人员下载和使用。从该项目获得的主要研究成果将在国内和国际会议上发表，并提交学术期刊发表。

This project focuses on two important image analysis problems. One is on image registration, which is to match up images or image volumes for structure localization, difference detection, and other purposes. It is widely used in medical imaging, remote sensing, finger print or face recognition, and so forth. The second major focus is on 3-D image denoising with edges and major edge features preserved. Because of fast progress in image acquisition techniques, 3-D images become increasingly popular in magnetic resonance imaging (MRI), functional MRI (fMRI), and other applications. However, observed 3-D images often contain noise, due to hardware imperfection and other reasons, which should be removed beforehand so that subsequent image analyses would be more reliable. In the literature, existing image registration (IR) methods can be roughly classified into two categories: feature-based IR methods and intensity-based IR methods. Because feature selection is often a time-consuming and challenging process, intensity-based IR methods have become popular in various applications. However, most existing intensity-based IR methods require a parametric model for describing the image matching transformation, which is often difficult to verify in practice. In this project, the investigator and his colleagues propose an intensity-based IR procedure without imposing any parametric form on the matching transformation. Therefore, the proposed method has the potential to greatly improve the intensity-based IR techniques and greatly broaden their applications. In the literature, most existing image denoising methods are for analyzing 2-D images. They often have certain ability to preserve planar parts of the edges, but cannot preserve angular parts of the edges well. Their direct extensions to 3-D cases generally cannot handle 3-D images efficiently, because the structure of 3-D images is often substantially more complicated than that of 2-D images. This project proposes a novel 3-D image denoising method which can preserve edges and major edge features well. Therefore, it would provide a reliable tool for 3-D image denoising.Images are used everywhere in our society, ranging from medical diagnostics by CT, MRI, and other medical imaging techniques to satellite monitoring of global environmental changes. This project aims to improve image registration and 3-D image denoising techniques, which are used broadly in various imaging applications. Thus, it will have broader impacts on our society through its direct impact on improvement of medical diagnostics, security systems involving fingerprint and face recognition, remote sensing techniques, and so forth. This project also aims to contribute to the development of human resources in science and engineering through its educational activities. For instance, the investigator offers an advanced topics course on image analysis, from which graduate students from various departments can receive systematic training in scientific research. Several graduate students are doing their thesis research with the investigator on image processing. Some computer software packages developed by the investigator and his graduate students would be posted on a project web page for other researchers to download and use. The major research results obtained from this project would be presented in national and international conferences, and be submitted for publication in academic journals.