插帧

图像修复是图像处理的一个重要问题。这是一个困难的问题，同时填写在地区缺少图像信息的纹理和结构。以损坏的图像inpaint失踪的结构和纹理信息，基于小波分解的图像修补算法提出。首先损坏的图像分解成子图像和纹理结构，利用小波子图像转变。然后，地区结构中缺少的信息的子图像重建曲率驱动扩散（CDD），算法，而在同一区域的纹理子图像填写基于改进的纹理合成的典范 最后，恢复的图像，通过重组，结构和纹理恢复的结果。大量的实验表明，该算法可以快速，高效地恢复在同一时间的结构和纹理信息，视觉效果和峰值信噪比比（PSNR）比同类算法更好。(Image inpainting is an important problem image processing. It is a difficult problem to simultaneously fill-in the texture and structure in regions of missing image information. In order to inpaint the damaged image with both missing the structure and texture information, an image inpainting algorithm based on wavelet decomposition is presented. First the damaged image is decomposed into structure sub-image and texture sub-image using the wavelet transformation. Then, the sub-image with the region of missing information in the structure is reconstructed by Curvature-Driven Diffusions (CDD) algorithm, while the same region in the texture sub-image is filled-in with the improved texture synthesis based on exemplar Finally, the restored image is given by recombining the structure and texture restored results. A large number of experiments show that the proposed algorithm can quickly and efficiently restore the structure and texture information at the same time, and the visual eff)

1、读取显示所给PET图像（SE2IM210）。 2、学习imhist函数，画出所给PET图像的直方图。 3、根据直方图为该PET图像选择合适的显示窗（imshow参数），使胸 部轮廓等解剖结构可见。 4、根据直方图选择合适阈值，分割肿瘤区域与正常区域，计算肿瘤区 域内图像灰度均值、方差、最大值及最小值。(1 give PET images displayed, read (SE2 IM210). 2, learning, imhist function, draw the give PET image histogram. 3, according to the histogram for the PET image to choose the appropriate display window (imshow parameters), make bosom Outline of anatomical structures such as visible. 4, according to the histogram, choose appropriate threshold segmentation tumor area and normal area, calculating the tumor area In the domain of image grayscale average and variance, the maximum and minimum values.)

散点图数据输入，绘制，输出整个过程， 对于文章出图很有帮助。(Scatter plot data entry, rendering, output the entire process, the article showing helpful.)

计算两幅图像之间的交叉熵，自己编的比较简单和大家分享。(Calculate the cross-entropy between the two images, their own series is relatively simple and to share.)

基于彩色信息的道路图象分割,可以有效的去除道路上的阴影.(Based on color information of the road image segmentation, can effectively remove the shadow on the road.)

用Kalman滤波方法对单个目标航迹进行预测，并借助于Matlab仿真工具，对实验的效果进行评估。 (Target tracking application context radar data processing, radar in the search to the goals and objectives of the record location data of the measured target position data (called a point of the track) processing, automatic formation flight path, and the target in the next The moment the position prediction. This article briefly discusses the Kalman filtering method to predict a single target track, and by means of Matlab simulation tools to assess the effect of the experimental.)

Pre-stack migration applied to GPR for landmine detection

多类图像特征结合上下文信息进行目标识别（分类、分割）(Many types of image features combined with context information for target identification (classification, segmentation))

压缩感知CS——采用小波变换进行稀疏表示，高斯随机矩阵为观测矩阵，重构算法为SP算法，对256*256的lena图处理，比较原图和SP算法在不同采样比例(0.74、0.5、0.3)下的重构效果，并各运行50次，比较算法性能PSNR和每次的运行时间(Compressed sensing CS- using wavelet transform as sparse representation, Gaussian random matrix as the observation matrix and SP algorithm as the reconstruction algorithm. Compare lena figure and the reconstruction results using SP algorithm at different sampling ratio (0.74,0.50.3),then each runs 50 times, compare the performance of PSNR and each running time)

斐波那契数的实现算法及分析,标准化实验报告样本()