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figure 4.2a single pluse 3-D uncertainty plot pulsewidth is 2 seconds。 Figure 4.2b. Contour plot corresponding to Fig. 4.2a. Figure 4.2c. Single pulse 3-D ambiguity plot. Pulsewidth is 2 seconds. Figure 4.2d. Contour plot corresponding to Fig. 4.2c. (figure 4.2a single pluse 3-D uncertainty plot pulsewidth is 2 seconds. Figure 4.2b. Contour plot corresponding to Fig. 4.2a. Figure 4.2c. Single pulse 3-D ambiguity plot. Pulsewidth is 2 seconds. Figure 4.2d. Contour plot corresponding to Fig. 4.2c.)

通过多尺度分解，实现医学图像的图像融合，达到更好的效果(Through multi-scale decomposition, medical image fusion can be achieved to achieve better results.)

SSIM函数。一种衡量两幅图像相似度的新指标，其值越大越好，最大为1。(SSIM function. A measure of image similarity two new indicators, the greater its value better, a maximum of 1.)

对于传统去噪模型的大幅改进，之前的模型都会出现阶梯效应的现象，采取了新的模型对图像进行建模，有效改善了图像去噪图像修复等过程中引入的阶梯效应，而且一定程度上对于图像纹理的修复也有很大的作用(For significantly improve the traditional de-noising model, the model will appear before the phenomenon of the staircase effect, to take a new model for image modeling, effectively improved the staircase effect denoising image restoration process introduced, and to a certain extent for texture of repair also has a significant role)

RGB 颜色选择器，可以自由选择颜色，也可以用吸管吸取屏幕颜色色值，便于程序员们开发(RGB color picker, you can choose colors freely, or you can suck the color value of the screen with a straw, which is easy for programmers to develop)

说明：  数字图像处理：阈值分割及形态学处理，本程序出色的完成了图形提取，内容包括程序，讲解和运行结果(Digital image processing: segmentation and morphology threshold treatment, the procedure was completed excellent graphics extraction, including procedures and operations on the results of)

一种基于背景减法和帧差的运动目标检测算法(Based on background subtraction and frame difference moving target detection algorithm)

对视频进行基本的处理，例如载入视频，显示视频，控制播放(Basic video processing, such as loading the video, show video, control playback)

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)

特征点匹配时，采用构造KD-tree，用最优节点优先法寻找最佳匹配点(Matching feature points, the tectonic KD-tree, with the optimal node is preferred method to search for the optimal matching point)