【作者】 江涛；

【导师】 林宗坚；

【作者基本信息】 山东科技大学 ， 大地测量学与测量工程， 2005， 博士

【摘要】 图像超分辨率处理技术是指利用多帧关于同一视域的有相互位移的低分辨率降质图像来重建高分辨率高质量图像的技术。图像超分辨率处理技术可突破图像采集设备的分辨率限制,充分利用多帧图像之间的有限冗余互补信息,实现亚像素级的图像信息融合。图像超分辨率重建在遥感、军事、医学成像、公共安全等领域有很广泛的应用前景。它可以在一定程度上消除由于图像离散化和图像退化引起的空间分辨率下降的不利影响,弥补原有图像空间分辨率的不足,获得更加清晰的图像,可使输出图像的质量得到很大程度的提高,既改善图像的视觉效果,又便于计算机对图像进行处理、分析和理解。 本文围绕图像超分辨率重建研究了相关的频率域和空间域超分辨率重建算法、图像配准算法、运动参数估计等内容。并取得一系列有意义的研究成果,主要工作体现如下: 1、对影像超分辨率重建的基本理论和技术实现进行了比较全面、客观的论述;分析了影像的成像过程及成像模型;探讨了影像超分辨能力及其超分辨的可行性; 2、基于影像灰度和影像特征的匹配方法,分析了影像形变的连续性特征和特征点高精度提取与匹配技术及其算法,对影像间的运动模型估计的块匹配和光流场方法进行了较为详尽的描述。提高了运动参数估计的精度和效率,为影像的超分辨率重建奠定了基础; 3、在分析了小波多分辨率分析与正交小波变换理论的基础上,提出基于小波和的主成份分析(PCA)结合的超分辨率重建算法,并将该算法成功应用于遥感影像超分辨率重建中,在应用上具有创新性; 4、对MAP和POCS这两种空间域方法进行研究,总结了其基本思想与算法流程。在此基础上针对该方法进行了试验,试验结果表明该方法能在影像超分辨率重建中取得比较明显的超分辨率重建效果,在应用上具有创新性; 5、对频率域解混叠方法的理论和算法流程进行了分析,从理论证明了其正确性和可行性,并从性能特点上与空间域方法进行了全面比较。 6、在共扼梯度最优化迭代算法中,对相机模型、图像微位移和微旋转角精确配准、共扼梯度重建等关键技术进行了研究。实验结果表明共扼梯度最优化迭代算法是鲁棒的、快速收敛的,并且大量节省内存。此算法易于扩展,使多传感器数据重建成为可能。 7、本文提出了对图像融合效果进行定量评价的方法和准则,并利用这些评价准则对更多还原

【Abstract】 Image super-resolution (SR) processing is the technology to reconstruct high resolution and high quality image(s) from a group of warped, blurred and noised low resolution images about the same scene. It breaks through the resolution limit of image acquisition equipment and can achieve data fusion on subpixel level. Image SR processing has proved to be useful in many practical applications, such as remote sensing, military detection, medical imaging, machine vision and public security, etc. It can greatly improve spatial resolution and enhance image quality. So it is beneficial for computer to process, analyze and understand the image.The main contents and contributions of this dissertation are as follows: 1 .A comprehensive review of the basic theories and techniques of super-resolution is addressed . The process of acquiring images and the model are analyzed briefly and the SR ability and feasibility are discussed.2. Based on the method of grey level and feature of image, smooth geometric distortion and high accuracy feature point extraction and matching algorithm are discussed in digital photogrammetry, and the way of block matching and optical flow field is described to improve the efficiency of image registration on motion estimation between images, which lays a good foundation for images super-resolution.3. Based on the multiresolution analysis with orthonormal wavelets, the wavelet super-resolution algorithm for the more general camera motion model is analyzed. The implementation of this algorithm to the super-resolution for remote sensing image is a great progress4. The basic theories and procedure of the MAP method and POCS method in spatial domain are summarized. These methods are applied for the super-resolution for images successfully and better super-resolution reconstruction results are obtained. It is a progress made in applications for image super-resolution.5. The theories and procedures of super-resolution via alias removal are analyzed, the correctness and feasibility of this method are proved in theory, and the method compared with spatial field on the capability.6. In conjugate gradient optimization algorithm, the continuous and digital models of an imaging system are defined to explain image acquisition, the image registration algorithm and the conjugate gradient reconstruction algorithm are designed. Experiment results show that the conjugate gradient reconstruction algorithm is robust, rapid convergent, and memory saved. This algorithm is prone to be extended and make it possible that multiple sensor data fusion constructs high resolution images.7. A series of experiments on image reconstruction are given in the thesis and some worthy conclusions are obtained. The experiment and calculation results show that the reconstruction schemes and evaluation criteria are effectual.更多还原