GPEXPAND-and-GPREDUCE

单目标定很好用的程序，对于单目摄像机的一个标定。张正友博士的方法，对于摄像机标定，切记标定板不能用手机拍摄，因为手机拍摄是变焦的(Single objective of the program is very good, for a single camera calibration. Dr. Zhang Zhengyou s method for camera calibration, remember that the camera calibration board can not be used to shoot the phone, because the phone is to shoot a zoom )

通信专业滤波算法中通过改变不同的观测角计算接受信号的信噪比。(Communications professional filtering algorithm by changing the different observation angle calculation to accept the signal-to-noise ratio.)

说明：  基于L1范数的多帧图像超分辨率图像重建算法，在原有算法基础上改进，提高重建精度和效率。(Based on the L1 norm of the multi-frame image super-resolution image reconstruction algorithm, the improvement on the basis of the original algorithm to improve the reconstruction accuracy and efficiency.)

RANSAC算法实现数据拟合，用此算法可以实现多视角图像匹配等(RANSAC algorithm for data fitting, using this algorithm can realize multi-angle image matching, etc.)

说明：  图像处理中常常提取的 一些特征向量的算法。(Extract feature vector)

利用侧抑制原理编写的一个最基本的小程序。程序实现了初步的轮廓提取效果。可供想要入门侧抑制原理的朋友参考。(The use of lateral inhibition, a basic principle of writing a small program. Program to achieve the initial contour extraction results. Introduction to principles of lateral inhibition for want of a friend for reference.)

加入乘性噪声和椒盐噪声的图像进行维纳滤波和均值滤波，采用不同窗口看效果(Add the image of multiplicative noise and salt and pepper noise for Wiener filtering and mean filtering, using different windows to see the effect)

用matlab基本语句实现直方图均衡化库函数histeq的功能(matlab histeq)

bandelet 去噪，包含blsgsm和平移不变去噪，不过对大图像需要的内存比较大(bandelet denoising, including blsgsm and translation invariant denoising, but for large images need more memory)

SURF算法作为一种新近出现的特征提取方法，在重复度、独特性、鲁棒性3个方面，均超越或接近以往提出的同类方法，并在计算效率上具有明显的优势。本代码采用SURF算法检测图像并进行坐标变换与图像拼接。 采用SURF算法对图像进行检测，其主要是用Hessian矩阵对图像进行检测，对图像的特征提取之后找到图像的特征点。之后采用最近临快速匹配（NN）、随机抽样一致性（RANSAC）算法和最小二乘法参数优化（LM）对特征点进行提纯匹配。最后在两幅图像中进行坐标变换，达到统一坐标系和图像拼接的效果。 (SURF（Speeded Up Robust Features） as a method of feature extraction which newly appeared is over or nearly previous method on duplication, uniqueness, and robustness and have a clear advantage on computational efficiency. This code uses the SURF and coordinate transformation algorithm to detect image and image matching. This code uses the SURF algorithm of image detection, the main is to use the Hessian matrix of image for testing, to find the image after image feature extraction of feature points. After we used Nearest Neighbor (NN), Random Sample Consensus (RANSAC) algorithm and least square parameter optimization for purification of matching feature points. Coordinate transformation in the last two images, to coordinate system to achieve the same image stitching. )