increasemap1

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)

图像匹配，在一副图象中搜寻子图像，寻找特征点(Image matching, in a sub-image search images to find the feature points)

数字图像处理，对彩色图像的拉普拉斯算子锐化以及梯度算子锐化的比较，VC/MFC实现。(Digital image processing, color image of the Laplacian and the gradient operator sharpening sharpening comparison, VC/MFC implementation.)

说明：  该gui函数基本上包括图像处理里面的最基本处理，相当于一个小型photoshop。比如读取文件，几何变换中的垂直镜像，平移，旋转，缩放；正交变换的DFT，FFT，DCT，DST，DHT，DWashT；灰度处理中的反色，直方图均衡，全局线性变换，分段线性变换，指数非线性变换，对数非线性变换；图像增强里面的加噪声，平滑，锐化，伪彩色增强；图像分割里面的灰度阈值法，Robert，Laplace，sobel，prewitt，canny算子边缘检测法；图像恢复里面的直接逆滤波，维纳滤波；图像编码里面的霍夫曼编码，行程编码等等(Basically, the gui functions including the most basic image processing inside the handle, which is equivalent to a small photoshop. For example, read the document, the geometric transformation of the vertical mirroring, shifting, rotating, zooming orthogonal transformation of the DFT, FFT, DCT, DST, DHT, DWashT anti-gray color processing, histogram equalization, global linear transformation , piecewise linear transformation, index of non-linear transform of the number of non-linear transformation image enhancement which increases the noise, smoothing, sharpening, pseudo-color enhancement the gray-scale image segmentation inside the threshold, Robert, Laplace, sobel, prewitt, canny edge detection operator method image restoration inside direct inverse filtering, Wiener filtering image coding inside the Huffman code, and so on Run-Length Coding)

asift算法进行图像配准，具有较好的结果，调试完成，可用(image registration, asift algorithm has a better result, debugging is complete, the available)

图片雾化效果 实例

活动目标检测源码,用混合高斯算法编写，适用于复杂场景视频监控(alive target detection，used in GMM algorithm)

无线传感器网络，泛洪算法。每一轮次每个节点向中心节点发送数据。最后的生成图像为节点的死亡数。(Wireless sensor networks, the flooding algorithm. Each round, each node sends data to the central node. The final generated image is the node numbers of death.)

该图像包含了各种细节、平滑区域、阴影和纹理，这些对测试各种图像处理算法很有用。(The image contains a variety of detail, smooth areas, shadows, and textures, which are useful for testing various image processing algorithms.)

说明：  matlab code for optimization