xa_context

数字图像处理,离散小波dwt变换域中水印的嵌入(digital image processing, discrete wavelet transform domain dwt watermark embedding)

YUV与RGB颜色空间之间的转换，转换效果很好的。(YUV and RGB color space conversion between the effect of a very good conversion.)

说明：  图像增强的目标是改进图片的质量，例如增加对比度，去掉模糊和噪声，修正几何畸变等；图像复原是在假定已知模糊或噪声的模型时，试图估计原图像的一种技术。 图像增强按所用方法可分成频率域法和空间域法。前者把图像看成一种二维信号，对其进行基于二维傅里叶变换的信号增强。采用低通滤波（即只让低频信号通过）法，可去掉图中的噪声；采用高通滤波法，则可增强边缘等高频信号，使模糊的图片变得清晰。具有代表性的空间域算法有局部求平均值法和中值滤波（取局部邻域中的中间像素值）法等，它们可用于去除或减弱噪声。 (A sharp and clear image is not directly produced from the optics, however, digital signal processing applied to the sampled image produces a sharp and clear final image that is also insensitive to misfocus related aberrations. This paper gives an overview of Wavefront Coding and example images related to the two applications of machine vision/label reading and biometric imaging. Design techniques of Wavefront Coding are unique from that of traditional imaging system design since both the optics and digital processing characteristics of the system are jointly optimized for optimum system performance.)

说明：  用PALKING模糊方法进行边缘检测，还有3个自适应改进方法(PALKING fuzzy method with edge detection, there are three adaptive Improvement)

N-FINDR算法 端元提取 读取MNF降维后的影像数据 读取MNF降维后的影像数据( using N-FINDR end-member extraction)

自己用MATLAB编的一维信号数学形态学的腐蚀与膨胀运算以及开闭运算，可用于滤去信号中的尖锐脉冲信号，适合于用于振动信号的预处理(Own series of one-dimensional signal using MATLAB mathematical morphology, corrosion and expansion of operations, as well as the opening and closing operation can be used to filter the signal sharp pulse signal suitable for vibration signal preprocessing)

说明：  recon基于双视图的人脸特征三维重建，一个视图为正投影，另一个是水平方向旋转，假定正交投影模型，getfeature用于从图像上标记特征点(facial feature reconstruction based on two views)

可见光图像飞机目标识别 模糊差影法 改进自适应阈值分割法 七阶Hu不变距(aircraft recognition)

用matlab实现了分形，效果还是不错的，是分形学习中的基础内容(Matlab realize the use of fractal, the effect is still good, is a fractal study based on content)

图像倒频谱生成并分析，可以用于运动模糊图像的PSF参数估计(Cepstrum image generation and analysis, can be used for motion-blurred image PSF parameter estimation)