BsplineCurve

图像保重要特征扩散滤波方法之-----非线性扩散(important feature images Bao proliferation filtering method----- Nonlinear Diffusion)

用matlab中各种不同方法对模糊图像进行复原，有维纳滤波，盲返卷积，Lucy-richardson方法，规则化复原图像等(Various different methods using matlab fuzzy image restoration, with Wiener filtering, blind convolution back, Lucy-richardson methods, rules-based recovery images, etc.)

调用标定好的双目摄像机，利用其内外参数进行立体匹配，计算所拍图像的视差，产生深度图(Call the calibrated binocular camera, use its internal and external parameters for stereo matching, calculate the parallax of the captured image, and generate depth map)

说明：  运用小波变换将图像从空间域转换到频率域，自己写的代码，欢迎讨论学习(Using wavelet transform to transform image from spatial domain to frequency domain)

超像素分割方法，在计算机视觉领域，图像分割（Segmentation）指的是将数字图像细分为多个图像子区域（像素的集合）（也被称作超像素）的过程。超像素有一系列位置相邻且颜色、亮度、纹理等特征相似的像素点组成的小区域。这些小区域大多保留了进一步进行图像分割的有效信息，且一般不会破坏图像中物体的边界信息。(Super pixel Segmentation method, in the field of computer vision, image Segmentation, Segmentation) refers to the digital image Segmentation region for multiple image sequence (the set of pixels) (also known as the pixels) process. Adjacent pixels have a series of position and features such as color, brightness, texture similar to that of small region composed of pixels. Most of these small area retains the further effective information for image segmentation, and generally does not destroy the boundary of the object in the image information.)

说明：  自己实现的BM3D图像去噪算法。它首先把图像分成一定大小的块，根据图像块之间的相似性，把具有相似结构的二维图像块组合在一起形成三维数组，然后用联合滤波的方法对这些三维数组进行处理，最后，通过逆变换，把处理后的结果返回到原图像中，从而得到去噪后的图像。(Image Denosing by Sparse 3-D Transform-Domain Collaborative Filtering.)

说明：  用于Inkscape扩展gcode文件使用(Use for Inkscape extended gcode file)

进行图像分解和图像融合的拉普拉斯金字塔matlab源程序(Image decomposition and the Laplacian pyramid image fusion matlab source)

绘制二维nurbs曲线，可以通过改变控制点或者权重从而改变图形的形状。(Draw a two-dimensional nurbs curve that changes the shape of a shape by changing the control point or weight.)

支持向量机在小波包去噪方法中的应用，小波包分解和svm相结合(Support vector machines in wavelet packet denoising of wavelet packet decomposition and combination svm)