nonmaxsup

快速鲁棒性Pca方法的一段matlab程序(fastrpca eneneneneen)

说明：  整理了五种多曝光图像融合的代码，用于图像处理，图像去雾，有英文介绍(Five kinds of multi-exposure image fusion codes are sorted out.For image processing, image defogging, with English introduction)

在图像分割中，FCM作为一种高效的分割方法收到广泛应用，FILCM分割算法是FCM算法的一种改进算法。(In image segmentation, FCM is widely used as an efficient segmentation method, and FILCM segmentation algorithm is an improved FCM algorithm.)

echarts-master  

论文介绍了一种SFS 算法的参数估计及其实现。它在考虑自遮掩影响的情况下, 有效地估计了SFS 算法中涉及的各种控制参数, 并引入亮度约束、灰度梯度约束和可积性约束, 计算出表面高度和表面向量, 实现三维重构。最后还指出了在Matlab 中实现需要注意的问题。(The paper introduced a SFS algorithm parameter estimation and its implementation. It under the condition of considering the covering effect, estimates the SFS algorithm effectively involved in all kinds of control parameters, and introduces brightness constraint, gray level gradient constraint and the integrability of constraints, calculate the surface height and surface vector, realize the three-dimensional reconstruction. Finally, points out the problems requiring attention is realized in Matlab. )

说明：  直方图均衡，图像去雾处理，是把原始图像的灰度直方图从比较集中的某个灰度区间变成在全部灰度范围内的均匀分布。直方图均衡化就是对图像进行非线性拉伸，重新分配图像像素值，使一定灰度范围内的像素数量大致相同。(Histogram equalization, image processing to the fog, is the original image histogram to a gray scale from the more concentrated into the full range of uniform distribution within the gray area. Histogram equalization is that the image is non-linear stretch, re-distribution of the image pixel values, so that a certain number of pixels within the gray area roughly the same.)

人脸图像质量评价体系介绍，非常全面，此方面研究的不错入门资料(Face image quality assessment system introduced, very comprehensive study in this regard a good introductory information)

本论文从CT图像重建原理入手, 根据迭代重建的物理意义, 从投影模型出发, 得到投影数据, 然后利用迭代算法MART 及SIRT 重建出断层图像, 再与模型相比较, 从而确定各算法的优劣, 总结出如何选择合适的图像重建算法。(Iterative Algorithms in Computed Tomographic Reconstruction)

Visual C /MATLAB图像处理与识别实用案例精选 胡小锋编着.pdf

说明：  实现SURF图像匹配，并将图片进行扭曲处理再次实现匹配。(Surf image matching is realized, and the image is distorted to achieve matching again.)