FFBP

可自选输入和参数的中值/均值/拉伸滤波，各项参数说明详见.m文件注释(Median/Average/Linear Stretch Filter)

MATLAB工具sift实现图像拼接，上下拼接(MATLAB tool sift image stitching, stitching up and down)

Harris角点检测程序（内附示例图像），利用鼠标在图像上选择提取交点的区域，进行角点提取。程序语言简洁，利于初学者学习。(Harris corner detection procedures (with sample images), using the mouse in the image on the choice of extraction point of intersection of the region, for Corner Detection. Programming language is simple and conducive to learning for beginners.)

本书系统地介绍了图像处理与识别的基本原理、典型方法和实用技术。全书共分12章，第1章～第6章是图像处理与识别的基础内容，包括图像科学综述、MATLAB语言图像编程、图像增强、图像分割、图像特征提取和图像识别；第7章～第10章是图像处理与识别的工程实例，涵盖了医学图像处理、文字识别和自导引小车路径识别等应用实例，并结合理论算法，提供了大量MATLAB代码程序，以帮助读者掌握如何使用MATLAB语言快速进行算法的仿真、调试和估计等方法。第11章～第12章，是两个综合性较强的实例，分别是Visual C++实现的基于神经网络的文字识别系统和车牌定位系统。 本书附带的光盘给出了各个章节列举的实例的源代码，同时赠送了28个常用数字图像处理算法的Visual C++代码实现。 本书讲解深入浅出，实例程序丰富，注重理论与实践相结合。本书可作为计算机应用、自动化、图像处理与模式识别、机电一体化专业的高年级本科生或研究生的参考书，也可供从事图像处理与识别的研究人员和工程技术人员阅读参考。(This book introduces the basic principles of image processing and recognition of the typical methods and practical skills . The book is divided into 12 chapters , Chapter 1- Chapter 6 is the basis of the content of image processing and recognition , including images scientific overview , MATLAB programming language images, image enhancement, image segmentation, image feature extraction and image recognition Chapter 7- Section Chapter 10 is a project example image processing and recognition , covering the medical image processing, character recognition and self- guided trolley path recognition example , the combination of theory and algorithms, for a lot of MATLAB code procedures to help readers learn how to use MATLAB language fast simulation , debugging and estimation methods algorithm. Chapter 11- Chapter 12 , are two examples of highly integrated , namely Visual C++ implementation based on neural network character recognition system and a license plate positioning system. The book)

文章讲诉的是小波在信号处理方面的应用，包括奇异点的检测，信号降噪等，有很全的原理介绍，有仿真程序和结论分析，具有一定的学习价值(V. article stresses that the wavelets in signal processing applications, including the singular point detection, signal noise, etc., have very wide introduction of the principle, procedure and conclusions have simulation analysis, has some learning value)

说明：  利用R语言编程实现高光谱遥感的随机森林分类(Random Forest Classification Based on Hyperspectral Remote Sensing Using R Language Programming)

Image Fusion With Guided Filtering基于向导滤波的图像融合。将图像分解成基础层和细节层，用一种新型的滤波融合图像，使融合效果更显著更高效。(The image is decomposed into a base layer and layer of detail, the fused image with a new filter, the fusion effect is more pronounced and more efficient.)

图像拼接，这是个图像拼接，还能说什么呢我的天是不是傻要字数限制(image fusion i have to think something to explain how to congraduation this website)

click energie of image , we can use it to calculate markov field ... and other

SSD: Single Shot MultiBox Object Detector, in PyTorch A PyTorch implementation of Single Shot MultiBox Detector from the 2016 paper by Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang, and Alexander C. Berg. The official and original Caffe code can be found here. Table of Contents Installation Datasets Train Evaluate Performance Demos Future Work Reference