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ISAR成像的最实用教材,采用matlab语言编写，包括源码(The best book about ISAR imaging,in matlab with resource codes)

链码直线检测，采用求取图像边界，然后边界跟踪，判别直线(Chain code line detection, to strike the image boundary, then the boundary tracking, discriminant linear)

数字音频水印的嵌入，提取，然后进行攻击性实验，检验其鲁棒性(Digital audio watermark embedding and extraction, and then attack experiment to test its robustness)

混合高斯模型提取视频帧前景背景图像，经试验验证准确率比较高(Mixed gaussian model to extract video frame prospects background image)

说明：  这是我们数字图像处理课程的大作业，我自己用matlabGUI做了一个界面，希望对大家有用，谢谢！(This is a large digital image processing program operations, for my own use matlabGUI made an interface and hope for all of us, thank you!)

Intel Ipp7.1的函数库很全的，还有用户手册，希望对大家有帮助。(Intel Ipp7.1 libraries very wide, as well as the user manual, we want to help.)

IEEE PAMI上一篇著名的Image Inpainting 算法MATLAB实现(Matlab implementation for a notable paper published on IEEE PAMI)

说明：  快速将图片裁剪为电脑壁纸和ipad壁纸尺寸，带预览(To cut pictures as PC or Ipad size conveniently)

可逆数字水印算法 Article (2009-Sachnev-IEEE_J_CASVT-989) Sachnev, V. Kim, H. J. Nam, J. Suresh, S. & Shi, Y. Q. Reversible Watermarking Algorithm Using Sorting and Prediction #IEEE_J_CASVT#, (Reversible watermarking Article (2009-Sachnev-IEEE_J_CASVT-989) Sachnev, V. Kim, H. J. Nam, J. Suresh, S. & Shi, Y. Q. Reversible Watermarking Algorithm Using Sorting and Prediction#IEEE_J_CASVT#, 2009, 19, 989-999 )

孔径雷达图像固有的相干斑噪声严重降低了图像的可解译程度，影响了后续目标检测、分类和识别 等应用。因此，SAR图像的相干斑抑制问题一直是SAR图像应用的重要课题之一。一个理想的去斑算法应该在平 滑的同时保持图像的边缘等细节不受损失，目前存在各种各样的算法，但没有一种方法能够完美的满足这一要求。 本文对SAR图像的相干斑抑制问题进行了全面系统的研究，分析了相干斑的形成原因，总结了目前存在的相干斑 抑制算法的主要思路，介绍了具有代表性的算法，并对各种算法的性能进行了定性分析和比较，给出了去斑算法定 量评估方法(The inherent speckle noise of the aperture radar image seriously reduces the degree of interpretation of the image, and affects the detection, classification and recognition of the subsequent targets. And other applications. Therefore, the problem of speckle suppression in SAR images has been one of the most important topics in the application of SAR images. An ideal speckle algorithm should be flat At the same time, the details such as edges of images are not lost. There are various algorithms at present, but none of them can satisfy this requirement perfectly.)