MATLAB_txtx1

图像分割 图像增长 边缘检测 医学图像分割 阈值分割(image segmentation iamge growing edge detection)

基于字典学习和矩阵低秩稀疏分解的SAR图像处理新方法，拓展了低秩稀疏分解的应用领域，有很好的应用前景。(Dictionary Learning and Low-rank Sparse Matrix Decomposition for Sparsity-driven SAR Image Reconstruction)

本书是第一本也是唯一一本详细介绍LOD(Level of Detail)的书。本书介绍了LOD的理论和多种实现的算法，讨论了LOD的实际应用，包括游戏编程中的优化、地形的优化等。本书是所有从事计算机图形领域的专业人士所必须参考的书，包括计算机游戏编程、医学可视化、计算机辅助设计，以及虚拟现实系统等等。(This book is the first and only one detail LOD (Level of Detail) book. This book introduces the theory and a variety of LOD realization algorithm, discussed the practical application of LOD, including game programming in the optimization, optimization, such as terrain. This book is all persons engaged in the field of computer graphics professionals who need to reference books, including computer game programming, medical visualization, computer-aided design and virtual reality systems.)

基于混合高斯的运动目标检测程序已经相应的文章！非常值得借鉴！(Gaussian mixture-based moving object detection procedures have been the appropriate article! Well worth learning!)

图像的圆检测程序。可以很好地进行灰度图的圆检测(Image circle detection procedures. Grayscale can be carried out of the circle detection)

系统地介绍总结了基于贝叶斯理论的陆海SAR图像分割(Systematic introduction summarizes the sea SAR image segmentation based on bayesian theory)

数字图像处理 小波处理 ，去噪音，比基于傅里叶变换的去噪方法好。 含噪信号经过预处理，然后利用小波变换把信号分解到各尺度中，在每一尺度下把属于噪声的小波系数去掉，保留并增强属于信号的小波系数，最后再经过小波逆变换恢复检测信号。(The noisy signal is pre-processed, then the signal is decomposed into different scales by wavelet transform. The wavelet coefficients belonging to noise are removed at each scale, and the wavelet coefficients belonging to the signal are retained and enhanced. Finally, the detected signal is restored by inverse wavelet transform. It is better than the denoising method based on Fourier transform.)

3d 图形学的 算法，包含源代码(3d graphics algorithms, including source code)

包含了主要的图像质量评价的matlab源程序。图像熵，图像的方差和，以及基于边缘检测算子的质量评价函数。(Contains the main image quality evaluation of the matlab source code. Image entropy, variance and images, as well as edge detection operator based on the quality of the evaluation function.)

说明：  这个是在运行的时候为了调试而写的，主要应用的场合是循环多，跟踪不方便的时候，记录到日志，引用了一个单元Unit_HBase,Unit_LogSp，已上传(this is the time to run the debugger and writing, the main application is a revolving occasions, tracking inconvenient time to record log, quoted a unit Unit_HBase, Unit_LogSp, uploaded)