matlab_smooth

Finding MSER regions and Canny edges in natural images

下面给出了48项泽尼克多项式，外加一项常数项。需要注意的是，读者并不需要严格按照下文所示的顺序排列这些泽尼克项，实际上在不同的应用和机构会采用不同的排列顺序。 表中的#0项是个常数或者说是平移项（piston term），这一项的系数也代表了平均光程差；而#1和#2项分别是x和y方向的倾斜项（tilt terms），#3代表了聚焦，因此，#1到#3项代表了波前的高斯或者近轴特性；#4和#5项代表了像散和离焦，#6和#7项代表彗差和倾斜，而#8项代表了3级像差和离焦，也就是说#4到#8项为3级相差项；同样地，#9到#15项代表了5级像差，而#16到#24项代表了7级像差，#25到#35项代表了9级像差，#36到#48项代表了11级像差。(Here are 48 Zernike polynomials, plus a constant term. It is important to note that the reader does not need to strictly arrange the Zernike entries in the order shown below, but in fact different orders of arrangement are applied to different applications and institutions. Table #0 is a constant or a shift (piston term), a coefficient of this term also represents the average optical path difference; while #1 and #2 are inclined X and Y direction (tilt terms), #3 represents the focus, therefore, #1 to #3 on behalf of the wavefront. Gauss or paraxial properties; #4 and #5 represent the astigmatism and defocus, #6 and #7 represent coma and tilt, and #8 represents the 3 order aberration and defocus, that is to say #4 to #8 is 3 level difference; similarly, #9 to #15 on behalf of the 5 order aberration #16 and #24, to represent the 7 level #25 to #35 aberration, on behalf of the 9 #36 to #48 aberration, on behalf of the 11 order aberration.)

Freeman链码（8方向）代码，进行图像边缘的描述，可用于基于内容的图像检索系统(Freeman chain code (8 directions) code)

纹理图像分割matlab程序，附带测试纹理图像图像，另外还有一篇高质量相关英文论文和一篇中文论文，供研究纹理分割的同学学习。(Texture image segmentation matlab, the supplementary test texture image image, in addition to a high quality related English papers and a Chinese paper, for research students texture segmentation study. )

说明：  图像颜色显著性，包含颜色直方图和颜色矩，是颜色显著性评价的重要内容(Image Color Salience)

基于压缩感知的图像加密算法，稀疏基用的是小波，重构用的是OMP(Compressed sensing image encryption algorithm)

图像旋转的MATLAB文件，角度可以定义，例子中包含了M源程序以及转换的图片。(MATLAB file image rotation, angle can be defined, for example, contains M as well as the conversion of the image source.)

alpha稳定分布噪声的matlab实现(alpha stable distribution noise matlab implementation)

内容为matlab的三维重建程序，达人可进来看，不适合初学者(Matlab says the three-dimensional reconstruction procedures, Tatsu can come watch, not suitable for beginners)

对各种不同的传感器测得数据进行融合处理，从而获得精确的环境信息，能够做出更正确的判断。这个是一位非常优秀的老师的课件，非常值得一看！是关于数据融合方面的(On a variety of sensor data fusion measured to obtain accurate environmental information to make more accurate judgments. This is a very good teacher of the courseware, is worth a visit! Data fusion)