WAV-LSB-Watermark

用于无参考图像质量评价，用MATLAB语言编写(For no-reference image quality evaluation)

图像配准,基于sift的图像配准程序，配准效果良好，运行速度快。(image match)

随机森林用于 图像处理matalab 代码(Random Forest matalab code for image processing)

kmeans算法实现，对图像处理。亲自使用过，可用，供参考。(Kmeans algorithm for image processing.)

说明：  八值图像连通区域标记，为每个连通区域分配一个唯一的标号，处理后的图像按照从左到右，从上到下的顺序获得连续的标号(Binary image connected region eight marks, for each connected region a unique label distribution deal with in accordance with the image from left to right, from top to bottom order of access to continuous labeling)

梯度倒系数实现背景抑制,提高小目标检测的信噪比(reversing Coefficients gradient background suppression, and enhance the signal-to-noise ratio target detection)

基于核函数的SAR图像目标识别,利用KPCA对SAR图像进行特征提取(SAR image target recognition based on kernel function，Use KPCA SAR image feature extraction)

说明：  去噪模型TV,可用于图像去噪，效果良好，模型特别简单(The denoising model TV can be used for image denoising, the effect is good, and the model is particularly simple.)

说明：  该课题为基于MATLAB的汽车出入库识别系统，带有丰富的人机交互GUI界面。目前毕业设计选题中，传统的中规中矩的车牌识别不易得到高分，必须要在此基础上有所创新方得可以避开其他雷同课题，不会轻易被导师被否决而导致毕设不过。因此建议在车牌识别基础上加入多种方法的对比，看看哪种方法的精度高。虽然目前有很多方法的车牌识别，但是都是在各自的测试库里面测试的，比如测试的车牌图像不同，字符库不同，导致无法做对比。整个设计在一个GUI界面上完成。(This project is based on MATLAB vehicle in and out of the warehouse identification system, with rich human-computer interaction GUI interface. At present, in the topic selection of graduation project, the traditional regular license plate recognition is not easy to get high scores, so it is necessary to innovate on this basis to avoid other similar topics, and it will not be rejected easily by the tutor, leading to the failure of graduation project. Therefore, it is suggested to add a variety of methods on the basis of license plate recognition to see which method has high accuracy. Although there are many methods of license plate recognition, they are tested in their own test library, for example, the test license plate image is different, the character library is different, so it can not be compared. The whole design is completed on a GUI interface.)

基于暗通道先验理论的去雾算法，使用rgb暗通道计算大气光及透射率获得去雾图像(Since the scene radiance is usually not as bright as the atmospheric light, the image after haze removal looks dim. So we increase the exposure of J(x) for display.)