ruanyuzhiquzao

一个功能比较全面的图像处理系统，对初学者很有参考价值。(One features a more comprehensive image processing system, useful for beginners reference value.)

极化SAR图像处理中的目标特征矩阵分解程序(Polarization SAR image processing target characteristic matrix decomposition process)

这是TV模型最新的快速计算Matlab源代码，算法可以解决很多非线性扩散方程的计算。稳定性高，计算快。(This is the latest TV models fast calculation of Matlab source code, the algorithm can solve a lot of non-linear diffusion equation calculations. High stability, fast calculation.)

说明：  对限制对比度自适应直方图均衡化算法adapthisteq进行了解释。可用于图像增强(Contrast to the limited adaptive histogram equalization algorithm adapthisteq is explained. Can be used for image enhancement)

盲水印提取时不需要参考原始载体图像,在信息隐藏、版权保护等方面具有更广泛的应用前景。提出的盲水印算法在分块离散余弦变换(DCT)和离散小波变换(DWT)的基础上,利用关系双方DCT系数和DWT系数在受到攻击时具有相同变化趋势的特点,采用关系嵌入和量化嵌入的自适应选择嵌入策略,较大幅度地提高了盲水印提取的鲁棒性。同时在量化嵌入中采用抖动调制,实现了水印透明性和鲁棒性调节的便捷性。大量仿真实验结果表明该算法对噪声干扰、低通滤波、JPEG压缩、对比度增强等攻击有很好的鲁棒性和透明性。关键词 数字水印盲水印关系嵌入量化嵌入离散余弦变换离散小波变换 按这篇文章的算法，自己编的matlab,没有攻击时水印提取率为1，加水印后图像PSNR有45+，。有攻击后提取率也有0.9+。(Blind watermark extraction can be fulfilled without referring to the original host image. Therefore it hasmuch prospective applications in the fields of information hiding and copyright protection. Based on blocking Discrete Cosine Transform (DCT) and blocking DiscreteWaveletTransform (DWT), the proposed blind watermarking algorithm uses an embedding strategy of adaptively selecting either relationship embedding or quantization embedding. The relationship em- bedding comes from the observation thatboth themagnitudes of coefficients concerned in the relationship usually have thesame change trend when the image is attacked. This strategy remarkably improves the robustness ofwatermark extraction.In addition, dithermodulation is used in quantization embedding, bywhich the tradeoff between transparency and robus-tness ofwatermarking can be easily adjusted. Simulation results show that the algorithm is fairly robust against the attacks such as noise, filtering, compression, and contrast )

图像修复是对图像中破损区域进行信息填充，以减少图像破损所带来的信息损失的过程。 传统的图像修复方法需要依赖图像的具体结构来制定相应的修复方法，压缩感知理论的提出，使得可以利 用信号的稀疏性来对图像进行修复。基于K 奇异值分解（KSVD）与形态学成分分析（MCA，Morphological Component Analysis）的图像修复方法首先采用形态学成分分析方法对破损图像进行特征分析，将其分解 为结构部分和纹理部分；然后基于学习型字典KSVD分别对这两部分进行过完备字典训练；最后利用训练得 到的字典实现对破损图像的修复。相比于传统的图像修复方法，该方法具有适应性强、修复效果好等优点(Image inpainting is to fill the missing data in corrupted images and thus to reduce the information loss of damaged image. Traditional inpainting algorithms are dependent on specific structure of target images compressive sensing theory makes is possible to realized image inpainting with signal sparsity. This paper proposes a novel inpainting algorithm based on KSVD and MCA algorithm, which first decomposes the image into texture part and structure part, and then trains the two dictionaries for these two parts with KSVD and reconstructs the original image with these two trained dictionaries. Experiment indicates that the proposed algorithm is of better adaptability and performance as compared with traditional algorithms.)

Reversible data hiding in images

先将字符串转化为像素图，再将像素图还原成二维数组。将二位数组转化为布尔数组。然后用一个顺序结构，第一帧放入比较程序，即显示汉字并闪烁程序。第二帧循环移位程序。第三帧屏幕关闭程序。(First string into a pixel map, and then reduced to a two-dimensional array of pixel map. The two-digit group into a Boolean array. Then a sequential structure, comparing the first frame into the program, the program that displays characters and flashes. The second frame cyclic shift procedure. The third frame of the screen to close the program.)

用其中一半的数据采用ANN-BP算法设计分类器，另一半数据用于测试分类器性能。(Half of them with the data ANN-BP algorithm design classifier, and the other half data used to test the performance of classification. )

说明：  小波去噪 matlab小波去噪详解超全超全有程序,小波去噪，硬阈值软阈值(Wavelet denoising Matlab wavelet de-noising details super full super full program, wavelet de-noising, hard threshold soft threshold)