jpeg_quality_score

求一个图像的最大内接矩形面积。 步骤： 1.相机标定。首先根据物像关系式求出其中的参数。注意参数求出后要进行参数校验。 2.从背景中分离出目标 3.边缘检测 4.目标形状参数计算。(For an image of the largest inscribed rectangle area. Steps: 1. Camera calibration. First of all object-image relationship in accordance with the parameters obtained. Attention to the parameters obtained after parameter calibration. 2. From the context of isolated target 3. Edge detection 4. Target shape parameters.)

用sift算子对两幅图像进行特征点的自动搜索。(Sift operator with the image feature point english)

静态图片转化为动态图片，把静态的图片转化为动态的(convert PNG picture to GIF picture)

高光谱图像的分类，适合各种光谱数据或者RGB图像。只需要调整输出路径就好了。(Hyperspectral image classification, for a variety of spectral data or RGB images. Only you need to adjust the output path just fine.)

说明：  NDVI最大值合成法批量计算Python代码(Python Code for Batch Computing by NDVI Maximum Composition Method)

Real-time Specular Highlight Removal实现论文“Real-time Specular Highlight Removal Using Bilateral Filtering”中算法(Real-time Specular Highlight Removal Papers " Real-time Specular Highlight Removal Using Bilateral Filtering" in the algorithm)

Retinex算法对较暗区域的图像处 理有明显效果,改进的Retinex方法则是基于经典Retinex,对具有较高亮度的遥感图像通过图像变 换方法达到去除模糊的目的。 (Retinex algorithm for image processing on the dark region was effective to improve the Retinex method is based on the classic Retinex, on remote sensing images with high brightness achieved by an image transformation method aims to remove ambiguity.)

出自较新的国际会议论文的图像去噪算法实现。对自然图像的去噪非常有效，即可以自己实际使用，也可以进一步研究学习。(From a relatively new international conference papers realize the image denoising algorithm. Denoising of natural images are very effective, that is their actual use, can also further study.)

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)

meanshift聚类，找到聚类中心,以及数据的类别(Clustering meanshift to find cluster centers, as well as the type of data)