WenLiLiJiaophoto

现有自然图像素描画效果生成算法存在容易造成画面细节丢失，笔画线条单一等问题。针对这些问题，本文提出了一种改进的自然图像素描画效果生成算法，通过模拟艺术家创作素描画过程，分步生成素描画图像底纹和素描画场景笔画轮廓，采用8个方向卷积滤波提取图像中不同方向的细节信息，并使用不同长度不同粗细的笔画来模拟艺术家在创作过程中不同力度的绘画效果，最后合并素描画笔画效果和素描画图像底纹，得到与原输入自然图像内容一致，色调与艺术家绘制的素描画效果相同，笔画和底纹形式与实际素描画相似，真实感较强的素描画效果输出图像。大量实验结果表明本文方法可以生成高质量的自然图像素描画效果，与现有成熟的铅笔画生成技术相笔，本文方法具有较强的可比性。(The existing algorithms for natural image sketch production are easy to cause some problems such as the loss of image details, singleness of the stroke line. To solve these problems, this paper proposes an improved algorithm for the natural image sketch effect producing. By simulating the artist creation process of sketch, step-by-step generate image shading sketch image shading and drawing the scene outline stroke of the sketch image, using 8 directions of convolution filter to extract the details of different directions in the image, furthermore, using the stroke of different length and thickness to simulate the painting effect of different strength in the process of artist creation, finally we merge the sketch stroke effect and sketch image background to get the output image, which have consistent content with the original input image, have the same tonal effect with artists draw sketch, have the similar Stroke and background form with the actual sketch and have strong real sense in)

数字图像处理（MATLAB版）（第二版）的工具箱，m文件(Digital image processing (MATLAB version) (Second Edition) toolbox, m file)

K均值聚类算法对图像进行分割，实验用程序，亲测可用。(K-means clustering algorithm for image segmentation, experimental procedures, pro-test is available.)

一个颜色直方图的matlab源码，备注非常详细，可以实现(A color histogram matlab source code, notes are very detailed, can be achieved)

说明：  利用特征提取和分类的方法,假设输入值为{大,圆,光滑}为水果的三个特征值,来代表三种不同的水果,识别苹果\梨\香蕉\桔子\菠萝水果类别. (The use of feature extraction and classification methods, assuming that the import value was (large, round, smooth fruit) for the three characteristics of value, to represent three different types of fruit, to identify Apple \ pear \ banana \ orange \ pineapple fruit category.)

说明：  基于cs的sar成像仿真，包括omp、sl0、osl0、onsl0等cs算法(ISAR imaging simulation based on CS, including OMP, sl0, osl0, onsl0 and other CS algorithms)

VC和MATLAB混合编程实现快速傅立叶变换(VC and MATLAB programming Fast Fourier Transform Mixed)

编程实现图像傅立叶变换和反变换，实现图像去除噪音(Programming image Fourier transform and inverse transform, image de-noise)

介绍了混合高斯背景建模法提取运动目标的过程，自己写的，比较好理解，付视频一个，用自己的视频也可以(Describes the process of Gaussian mixture background modeling method to extract moving target, write your own, is better understood, paid a video, you can use your own videos)

SIFT，即尺度不变特征变换（Scale-invariant feature transform，SIFT），是用于图像处理领域的一种描述。这种描述具有尺度不变性，可在图像中检测出关键点，是一种局部特征描述子。[1] 该方法于1999年由David Lowe[2] 首先发表于计算机视觉国际会议（International Conference on Computer Vision，ICCV），2004年再次经David Lowe整理完善后发表于International journal of computer vision（IJCV）。截止2014年8月，该论文单篇被引次数达25000余次。(SIFT, namely Scale Invariant Feature Transform (Scale-invariant feature transform, SIFT), it is a description for image processing. This description has scale invariance, can detect critical point in the image, it is a local feature descriptor. [1] The method in 1999 by David Lowe [2] First published in the International Conference on Computer Vision (International Conference on Computer Vision, ICCV), 2004 was again perfect finishing after David Lowe published in the International journal of computer vision (IJCV) . As of August 2014, the paper cited the number of times a single article of more than 25,000 times.)