harris

精心收集的几个去噪算法，包括基于视觉的非线性去噪、BLS_GSM算法、NL-Bayes图像去噪、KSVD去噪等，内容为核心代码，需要配置完善。 (Denoising algorithm of several carefully collected, including visual based nonlinear denoising, BLS_GSM algorithm, NL-Bayes image denoising, KSVD denoising, the content as the core code, the need to improve the allocation of. )

介绍qbic图像处理工具的详细文档，如有兴趣请看看(Introduction qbic detailed documentation of image processing tools and, if interested please take a look)

该算法实现了通过霍夫变换提取直线和圆，希望对大家有帮助(This algorithm can extract line and circle through hough conversion.)

利用高斯混合模型进行视频前景运动目标的提取！请使用自己的AVI文件。(extract the foreground moving object using the Gaussian mixture model)

Image Edge Enhancing Coherence Filter Toolbox，各向异性非线性扩散滤波器(This toolbox will perform Anisotropic Non-Linear Diffusion filtering on a 2D gray/color or 3D image. This filtering will reduce the image noise while preserving the region edges, and also enhancing the edges by smoothing along them. This is one of the more advanced image enhancement methods available, and also contains HDCS from october 2009. The result looks like an artist painted the image, with clear brush strokes along the image edges and ridges, see screen-shot. )

实现了基于关键像素点的FLICM图像分割算法，关键像素由局部最大值方法提取。(A FLICM image segmentation algorithm based on key pixels is implemented. Key pixels are extracted by local maximum method.)

傅里叶振幅相位恢复工具箱，包括经典的ER、HIO算法(toolbox of Fourier magnitude phase retrieval in matlab, including ER, HIO algorithms)

在MATLAB中，信号S经过信道H卷积后生成接收信号V，V＝conv(S,H),从V和H反卷积(In MATLAB, the signal S after convolution H channel generated receive signal V, V = conv (S, H), from V and H deconvolution)

将颜色图像的色彩迁移到灰度图像中，采用的算法为welsh算法，有较好的效果；该程序是在VC++6.0的环境下调试实现的，能将颜色图像的颜色较好的迁移到灰度图像中.(Migration of the color image to gray image in color, using the algorithm for the welsh algorithm, better results the program in VC++6.0 environment debugging to achieve, can color the better the color of the image transfer to the gray image.)

数字图像处理实验-图像处理-含实验题目及源代码(Pseudo-Color Image Processing (a) Implement Fig. 6.23, with the characteristic that you can specify two ranges of gray-level values for the input image and your program will output an RGB image whose pixels have a specified color corresponding to one range of gray levels in the input image, and the remaining pixels in the RGB image have the same shade of gray as they had in the input image. You can limit the input colors to all the colors in Fig. 6.4(a). (b) Download the image in Fig. 1.10(4) and process it with your program so that the river appears yellow and the rest of the pixels are the same shades of gray as in the input image. It is acceptable to have isolated specs in the image that also appear yellow, but these should be kept as few as possible by proper choice of the two gray-level bands that you input into your program.)