rsplit

雾天图像处理，利用暗原色先验进行图像处理。(dark channel prior)

维纳滤波，图像恢复，通过用matllab编辑的程序实现以上功能-wena (Wiener filtering, image restoration, with matllab editing program to achieve the above functions-wena)

捷联惯性导航姿态解算原理及核心算法,从原理到最终程序实现(Strapdown inertial navigation attitude algorithm principle and the core algorithm, the principle to the final program)

进行图像区域合并操作,能够较为有效，较好的进行图像合并(combine the image，very effcient)

应用于fluent的UDF程序，用于修正液滴表面轮廓(The UDF is applied fluent procedures for correcting the droplet surface contour)

移动窗口算法平滑光谱矩阵，用于近红外等光谱数据的预处理(Moving window spectral matrix smoothing algorithm for near-infrared spectral data, such as the pretreatment)

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 )

Contrast Stretching in Matlab

说明：  LMMSE图像超分辨率重建，基于先验知识的图像超分辨率重建(LMMSE image super-resolution reconstruction, image super-resolution reconstruction based on prior knowledge)

此程序为袁晓彤CVPR论文“基于多任务联合稀疏表示的的视觉分类”的主代码部分(The program for Yuan Xiaotong CVPR paper " visual classification with Muti-task joint sparse representation" main code of the parts)