Producing-Letters-on-7Segment

本程序对同一图像增加噪声后，进行均值滤波、高斯平滑滤波和中值滤波三种方法的去噪和结果比较， 并进行了评价指标PSNR和SSIM的计算以及算法耗时的统计。 ( The program on the same image after the noise increases, mean filter, de-noising and results of the Gaussian smoothing filter and median filter three methods of comparison, and the index PSNR and SSIM calculation algorithm and time-consuming statistics.)

用PHD滤波的方法实现多目标跟踪，及对PHD滤波性能的检测。(PHD filter method using multi-target tracking, and performance testing for the PHD filter.)

边缘检测，并分割，以不同颜色标示。站内有其matlab实现，这是对应的c++代码。(Edge detection and segmentation, marked with different colors. Inside the station are the matlab realize, This is corresponding c++ code.)

说明：  此程序为地震层析成像的LSQR算法，此算法用来解反问题。(This procedure for seismic tomography LSQR algorithm, the algorithm used to solve inverse problems.)

局部二进制模式，LBP，是已被用于纹理特征的一个 分类。在本文中，提出了一种基于使用这些功能的方法 检测缺陷图案的面料。在培训阶段，在第一个步骤LBP算子是 施加到无缺陷织物样品，逐个象素和参考的所有的行（列） 特征矢量的计算。那么这个图像被分为Windows和LBP算子是 应用这些窗口的每一行（列）。根据与参考比较 特征向量一个合适的阈值，无缺陷的窗户被发现。在检测阶段中，一个 测试图像被划分成的窗户，并使用阈值时，有缺陷的窗口可以 检测到。该方法简单，灰度不变。由于其简单性， 线上实现是可能的。(Local Binary Patterns, LBP, is one of the features which has been used for texture classification. In this paper, a method based on using these features is proposed for detecting defects in patterned fabrics. In the training stage, at first step LBP operator is applied to all rows (columns) of a defect free fabric sample, pixel by pixel, and the reference feature vector is computed. Then this image is divided into windows and LBP operator is applied to each row (column) of these windows. Based on comparison with the reference feature vector a suitable threshold for defect free windows is found. In the detection stage, a test image is divided into windows and using the threshold, defective windows can be detected. The proposed method is simple and gray scale invariant. Because of its simplicity, online implementation is possible as well. )

MRF代码实现,visual C++ 代码，不错，可以尝试(an implementation of MRF)

用MATLAB实现的darkchannel算法，实现图像去雾(Image Haze Removal Using Dark Channel)

对于一张8位灰度图像lena.bmp 1）运用4×4抖动矩阵，生成对应抖动图像 2）生成有序抖动图像 3）对于一张24位彩色图像，生成4×4抖动图像( For a 8-bit gray image (lena.bmp) 1）Use a dithering matrix (4*4), generate the dithered image. 2) Generate the ordered ditering image (4*4). 3) For a 24-bit color image, generate the dithered image (4*4). )

说明：  当前论文主要考虑的是非信号依赖的高斯噪声下的图像恢复，本程序实现了泊松噪声下的图像恢复，泊松噪声为信号依赖噪声，能够更加有效逼近实际成像系统噪声。( This is the code that was used in the papers "A Nonnnegatively Constrained Convex Programming Method for Image Reconstruction", "Total Variation-Penalized Poisson Likelihood Estimation for Ill-Posed Problems", "Tikhonov Regularized Poisson Likelihood Estimation: Theoretical Justification and a Computational Method", "An Efficient Computational Method for Total Variation with Poisson Negative-Log Likelihood", "An Analysis of Regularization by Diffusion for Ill-Posed Poisson Likelihood Estimation," "An Iterative Method for Edge-Preserving MAP Estimation when Data-Noise is Poisson", and finally, "Regularization Parameter Selection Methods for Ill-Posed Poisson Maximum Likelihood Estimation". See my publications page for more details. The main algorithm is for nonnegatively constrained, regularized Poisson likelihood estimation. At this point you can choose Tikhonov, total variation regularization, and diffusion regularization. A number of other methods are also implemented. Regularizatio)

说明：  图像处理，运动放大，视频代码展示，以及输出结果(steerable pyramid algorithm)