SupResolDemo

博士论文，分数阶微积分在现代信号分析与图象处理中应用给出了详细的分析和探讨，论文覆盖面广，有着很多的实验结果和详尽的分析。(Ph.D. thesis, fractional calculus in a modern signal analysis and image processing application gives a detailed analysis and discussion, research papers covering a wide range, has a lot of experimental results and detailed analysis.)

说明：  [Wang 2011]The Meaning of Interior Tomography

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.)

基于数学形态学的图像颗粒度分析算法，先去噪再求面积然后绘制颗粒度函数。(based on mathematical morphology particle size analysis algorithms, first try to de-noising area before drawing particles function.)

根据指定字符分割字符串，VC++精选编程源码，很好的参考。(According to the specified character segmentation character string, VC++ select programming source code, a good reference.)

说明：  对线激光相机标定，使用matlab编程，里面带有数据集，写好的函数。(Calibration of line laser camera, programming with MATLAB)

1.运用Laplacian算子，基于二阶微分的图像增强，即拉氏变换法进行图像平滑 2.利用邻域平均法实现图像的平滑处理 3.利用Robert算子做锐化处理(1. The use of Laplacian operator, based on second-order differential of the image enhancement, that is, Laplace transform method for image smoothing 2. The use of neighborhood average method of smoothing image 3. The use of Robert sharpening operator to do)

文章对比分析了火焰不同的形状结构特征，及其特征组合对火焰检测有效性的影响，提出了一种融合圆形度、矩形度和重心高度系数的火焰检测算法，然后将融合后的火焰特征输入支持向量机(SVM)中进行分类( Based on fusion of these flame features，the support vector machine (SVM) is used for classi- fication． Experimental results on the fire videos at Bilkent University show that the proposed algorithm is efficient and fast for fire detection，and it could detect fire real-time under a variety of circumstances．)

全参考型视频质量评价方法，基于机器学习和视频特征提取，发表与2012年TMM(FR VQA method based on machine learning and video feature )

离散傅里叶变换、离散余弦变化、离散小波变换(Discrete Fourier transform, discrete cosine transform and discrete wavelet transform)