JOS

通过GAN和WGAN在python的tensorflow平台上实现图片生成，与真实图片基本一致。(Through GAN and WGAN, the image generation is realized on the tensorflow platform of python, which is basically the same as the real picture.)

2014年海康威视校招笔试题，对于想要从事图像处理工作的同学十分有用，图像处理算法类试题，考的是C语言和C++.图像算法类题目不常见。(2014 Hikivision exam)

6自适应波段选择高光谱图像融合使用互信息。国际会议信息融合2005 _guo_fusion_a(6 Adaptive band selection for hyperspectral image fusion using mutual information . International Conference on Information Fusion 2005_guo_fusion_a)

基于马尔科夫链的图像分割，较以往经典图像分割性能有很大提高(Markov chain-based image segmentation, image segmentation performance than the classical past has greatly improved)

基于Gabor小波变换的特征提取和人工智能的人脸检测系统源代码.(Based on the Gabor wavelet feature extraction and artificial intelligence face detection system source code.)

说明：  NISwGSP stitching . 新一代的图像拼接(image stitching new. more powerful than apap)

包含滤波模板，形态学运算，边缘检测结合经自己修改过的hough变换编写的vc程序，成功检测机场跑道和任何图像中最明显的现状特征，经测试，检测精度高。对学习vc编程用于图像处理有帮助。(hough transform based image processing package which is useful for detecting airfield like straight line features.)

C++ 写的一些算法模板 ，比如Kruskal、KMP、欧几里德算法、最大匹配(匈牙利算法)、最小费用最大流、字符串的哈希方法、增广路算法、网络最大流_邻接表等……(C++ write some algorithms template, such as Kruskal, KMP, Euclid arithmetic, maximal matching (Hungary) is proposed, the minimum cost and maximum flow, string hash method, augmented road algorithm, network maximum flow _ adjlink etc......)

提出了一种结合USFFT Curvelet 变换的各向异性扩散图像去噪模型。它有机结合了Curvelet 变换和各向 异性扩散（P-M扩散）两者的优点。通过P-范数方法选择合适的梯度阈值K，P-M扩散过程通过处理经过Curvelet 变换得到的图像的不同尺度的Curvelet 系数矩阵，实现了建立在对图像多尺度分析的基础上的新P-M扩散模型。 实验表明，新模型的处理结果能有效避免传统P-M 扩散出现的阶梯效应，同时更好地保留图像的纹理和细节。 关键词：图像去噪算法；各向异性扩散；Curvelet 变换；P-M 扩散(Abstract: An image de-noising model by integrating anisotropic diffusion with USFFT Curvelet transform was proposed, which combined the strongpoint of Curvelet transform with anisotropic diffusion (P-M diffusion). By choosing appropriate gradient threshold K through p-norms and carrying out the P-M diffusion process depend on the different scale matrixes of Curvelet coefficient of the image from Curvelet transform iterations, as a result, the improved model made it possible to carry out the new P-M diffusion de-noising process based on multi-scale analysis of the image. The experiment results have demonstrated that the model can avert the stair-casing effect in the traditional P-M diffusion effectively and keep the textures and details of images better.)

C# 水平交错效果显示图像 实例