main_lee

转换图象为二值图象后，进行识别与标记的matlab源码。可以计算目标物个数，形心等。(image conversion value for the two images, identification and marking of Matlab source. Can be calculated from the number of goals, such as heart-shaped.)

实现图像的Contourlet变换，显示图像变换后每一层的图像。(Realize the Contourlet transform of the image , each layer of image is displayed after transform.)

脉冲耦合神经网络进行图像分割的matlab程序，利用PCNN点火捕获的相似性集群特性进行图像分割(Pulse Coupled Neural Net)

说明：   针对雾天下拍摄图像的退化现象，远景部分是一块灰度分布比较集中且接近天空亮度的区域，而近景部分可以分辨，其灰度分布比较分散。提出了一种基于遗传算法阈值分割的雾天图像增强方法；该方法首先用遗传算法求出近远景的分割阈值将图像分割[1]出来，然后对两个部分分别进行清晰化处理。(make the picture clear)

semi-supervised learning 半监督局部线性嵌入(semi-supervised learning )

高动态图像(HDR)合成算法，多曝光图像的配准算法(High dynamic image (HDR) synthesis algorithm, multi-exposure image registration algorithm)

说明：  基于Robert算子、Sobel算子、Prewitt算子、Log算子、Canny算子的边缘检测代码(Edge detection code based on Robert operator, Sobel operator, Prewitt operator, LOG operator and Canny operator)

contourlet变换工具箱，很好用的。(contourlet conversion kit, the good.)

题目： 八宝粥的生产过程中需要用到大量的红豆（红蚕豆），而实际上从红豆产地购买得到的红豆中会参杂一些杂物和不合格红豆。为了保证八宝粥的质量，需要对红豆进行筛选，去除不合格红豆和其它杂物。目前国内在红豆筛选工序上仍然使用人工筛选的方式，存在人工成本高、精确度差、劳动强度大等缺点。因此八宝粥生产厂商迫切需求开发一款能够自动实现红豆筛选的自动化筛选机。针对上述需求，请设计筛选机中的基于可见光图像的红豆筛选算法，该算法应尽可能的准确的找到参杂在红豆原料中的不合格红豆和杂物。 附件包括两个不同实验环境下拍摄得到的红豆相关图片样本库，实验环境分别为自然光照条件和灯光条件。每个条件下的样本库包括合格、不合格、杂物和混合四类样本的图像，其中合格、不合格以及杂物的图像可用来训练或建模，混合类图像用来测试算法的准确性和实时性。同学可在自然光照环境下的样本库或者灯光条件下的样本库中任选其一，用于解决上述问题。 作业提交格式包括以下四个内容： 一、 问题分析 二、 算法设计 三、 实验结果(将自己选择的样本库中的混合样本图片中的样本个体进行分类，并给出可视化的分类结果。) (Title:Use a lot of red bean production process of eight-treasure porridge ( red bean ), but in fact from the Red areas available in red bean can blend some sundries and unqualified red bean. In order to ensure the quality of eight-treasure porridge, the need for screening of red bean, red bean and other debris removal is not qualified. At present in the domestic bean screening process still use manual screening method, has the disadvantages of high labor costs, poor accuracy, high labor intensity. Therefore, eight-treasure porridge manufacturers need to develop a can achieve automatic bean screening automatic screening machine. According to the above requirements, please design screening machine selection algorithm based on visible light image of the red, the algorithm should be as accurate as possible to find the mixed in the bean raw materials in the unqualified red bean and debris.Accessories include captured in two different experimental environment of the red bean image sample dat)

图像融合质量评价指标，包含灰度值，平均梯度，光谱扭曲程度，SSIM，PSNR，MSE等等。(Image fusion quality uation, including gray value, average gradient, spectral distortion degree, SSIM, PSNR, MSE, and so on.)