elint

以SIFT特征为目标输入，LDAHash方法进行降维实现目标识别(SIFT features input LDAHash method to reduce the dimensionality of the target recognition)

本程序用于CurveLab-2.0水印技术的处理．(the procedures for CurveLab-2.0 watermarking technology management.)

Graphics PresentationsMandelbrot Set Function,

说明：  很好的图像边缘检测程序，MATLAB环境，里面的程序我都试过了，无报错，并附带图片，可直接运行。(Good edge detection procedure, MATLAB environment, which I have tried the procedure, and without error, and attached picture, can be directly run.)

去噪，一个非常好的去噪源代码，简单好用，设置方便(Denoising, denoising source code is a very good, easy to use and easy set up)

说明：  关于图像处理里的一些应用，将视觉相应算法应用到工程实际中，详细解说了算法在这里面的一些应用，很实用。(On some applications in image processing, the visual corresponding algorithm is applied to the engineering practice, a detailed explanation here below in some applications, the proposed algorithm is very practical.)

画椭圆和圆和直线的二值图求边缘点斜率(Draw the ellipse and the circle and the straight line of the binary image to find the edge slopeDraw the ellipse and the circle and the straight line of the binary image to find the edge slope)

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. )

图像质量评价，熵、平均梯度、边缘强度、方差等(Image quality evaluation, entropy, average gradient, edge strength, variance, etc.)

利用小波变换的去噪程序！和中值滤波进行对比！(The use of wavelet transform denoising procedure! And median filtering comparison!)