【作 者】Per Christian Hansen 【出版社】Society for Industrial and Applied Mathematic 【出版日期】October 29, 2006 【ISBN】0898716187 9780898716184 【形态项】9.8 x 6.7 x 0.3 inches 【语 言】English 【价 格】$63.00 Deblurring Images: Matrices, Spectra, and Filtering (Fundamentals of Algorithms 3) (Fundamentals of Algorithms) By Per Christian Hansen Publisher: Society for Industrial and Applied Mathematic Number Of Pages: 130 Publication Date: 2006-10-29 ISBN-10 / ASIN: 0898716187 ISBN-13 / EAN: 9780898716184 Binding: Paperback “The book’s focus on imaging problems is very unique among the competing books on inverse and ill-posed problems. …It gives a nice introduction into the MATLAB world of images and deblurring problems.” — Martin Hanke, Professor, Institut für Mathematik, Johannes-Gutenberg-Universität. When we use a camera, we want the recorded image to be a faithful representation of the scene that we see, but every image is more or less blurry. In image deblurring, the goal is to recover the original, sharp image by using a mathematical model of the blurring process. The key issue is that some information on the lost details is indeed present in the blurred image, but this “hidden” information can be recovered only if we know the details of the blurring process. Deblurring Images: Matrices, Spectra, and Filtering describes the deblurring algorithms and techniques collectively known as spectral filtering methods, in which the singular value decomposition—or a similar decomposition with spectral properties—is used to introduce the necessary regularization or filtering in the reconstructed image. The concise MATLAB® implementations described in the book provide a template of techniques that can be used to restore blurred images from many applications. This book’s treatment of image deblurring is unique in two ways: it includes algorithmic and implementation details; and by keeping the formulations in terms of matrices, vectors, and matrix computations, it makes the material access

经典beamforming、自适应滤波教材matlab源代码。 Paulo S.R. Diniz编著的自适应滤波第四版（Adaptive Filtering_Algorithms and Practical Implementation 4th），源代码——Nonlinear_Adaptive_Filters

本代码为自适应局部迭代滤波（ALIF）处理振动信号，内有可运行的示例（demo文件），添加了相关注释，matlab2018可以直接运行，其他版本请自行尝试。ALIF是2016年Antonio Cicone提出的一种自适应信号处理方法，原作者论文已附在压缩包中，代码中的示例效果并不代表最佳效果，只作为运行展示使用。

Multirate signal processing techniques are widely used in many areas of modern engineering such as communications, digital audio, measurements, image and signal processing, speech processing, and multimedia. Multirate Filtering for Digital Signal Processing: MATLAB Applications covers basic and advanced approaches in the design and implementation of multirate filtering. This authoritative volume considers the role of filters in multirate systems, provides efficient solutions of finite and infinite impulse response filters for sampling rate conversion, and discusses examples of multirate multilevel filter banks, offering a must-have book for practitioners and scholars in multirate signal processing.

The definitive textbook and professional reference on Kalman Filtering - fully updated, revised, and expanded This book contains the latest developments in the implementation and application of Kalman filtering. Authors Grewal and Andrews draw upon their decades of experience to offer an in-depth examination of the subtleties, common pitfalls, and limitations of estimation theory as it applies to real-world situations. They present many illustrative examples including adaptations for nonlinear filtering, global navigation satellite systems, the error modeling of gyros and accelerometers, inertial navigation systems, and freeway traffic control. Kalman Filtering: Theory and Practice Using MATLAB, Fourth Edition is an ideal textbook in advanced undergraduate and beginning graduate courses in stochastic processes and Kalman filtering. It is also appropriate for self-instruction or review by practicing engineers and scientists who want to learn more about this important topic.

自适应滤波算法与实现(第四版)，英文版，Paulo S. R. Diniz，2013

何凯明 引导滤波 以及 快速引导滤波 相关论文、PPT以及代码。 引导滤波：即需要引导图的滤波器，引导图可以是单独的图像或者是输入图像，当引导图为输入图像时，引导滤波就成为一个保持边缘的滤波操作，可以用于图像重建的滤波。

stereo matching using tree filtering 是杨庆雄老师的一个论文代码，关于立体匹配，发表在PAMI，同时是non-local的扩展

动 机： 利用图像I的局部信息去滤波图像q。 目 标： 使得图像q保持图像I所具有的局部信息。 本 质： 将空域滤波模型推广到基于图像信息的滤波。

Fundamentals of Kalman Filtering: A Practical Approach