imsave

说明：  这个源程序的主要功能是实现图像基于拉普拉斯金字塔的图像融合(The primary function of the source image is Laplacian pyramid-based image fusion)

说明：  基于压缩传感的图像处理，其中运用了迭代的方法，不错的文章(Based on compressed sensing image processing, which used the iterative approach, a good article)

说明：  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)

在复杂背景下的多目标检测算法的研究与源代码(In the complex context of multi-target detecting algorithm and source code )

Sobel算子就是一种基于方向导数掩模求卷积的方法。通过边缘检测算子可以检测到每个像素的领域并对灰度变化率进行量化，也包括方向的确定。该代码是基于sobel算法的检测程序。(Sobel operator is a directional derivative mask and convolution methods. To each pixel and gray level in the field rate of change can be detected through the edge detection operator to quantify, including direction. The code is based on sobel algorithm testing procedures.)

泊松融合在某种意义上解决了图像融合的问题，但其在融合的过程中仅仅考虑了融入图像的梯度，而没有利用背景图像的梯度，因此，在使用泊松融合的过程中，需要对融入区域的标记较为准确，否则，会造成背景纹理的丢失，视觉上可以明显觉察图像融入的痕迹。因此，对公式稍作修改，在考虑前景的同时考虑背景的变化，可以得到更优的结果。(Poisson convergence in a sense solved the problem of image fusion, but it only considers the integration of image gradient in the integration process, but not the use of a background image gradient, therefore, the use of the Poisson integration process, the need for more accurate marker into the area, otherwise, it will result in the loss of background texture, image integration can clearly perceive the visual traces. Therefore, the formula slightly modified, in considering the prospect of taking into account the changes in the background, you can get better results.)

复杂场景中的红色交通标志牌检测与识别，结合颜色与圆形的标志牌定位，然后提取特征，最后用模板匹配的方法实现识别，内附图片和程序说明，对初学者有帮助(Red detection and recognition of traffic signs in complex scenes, the combination of colors and circular signs positioning, and feature extraction, the last with template matching methods to achieve recognition, included pictures and a description of the procedures for beginners)

包滤波器，主要功能是在给定的滑动窗口大小下，对每个窗口内的像素值进行相加求和(Packet filter, the main function is given under the sliding window size for each window of the pixel values ​ ​ summed)

是图像处理中常用的测试图库，非常实用,如lena图片， 青椒图片，以及zelda图片等(is the test pictures used in image processing very useful)

PCA+SVM，对图像进行降维分类，并在yale库上测试取得比较好的效果(PCA+ SVM, dimensionality reduction of image classification, and yale library to achieve better test results)