suanshubianma

在idl环境下，用最佳指数法对高光谱图像进行波段选择的程序(OIF)

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.)

采用了小波去噪的思想，已经调试成功.内含m文件，可直接运行，用于建立主成分分析模型。( Using wavelet denoising thought, Has been successful debugging. M contains files can be directly run, Principal component analysis model for establishing.)

论文《Enhancing The Low Quality Images Using Unsupervised Colour Correction Method》提出的算法代码(algorithm code of pape《Enhancing The Low Quality Images Using Unsupervised Colour Correction Method》)

核自适应滤波算法krls的matlab程序。已将klms算法弄成函数，加载即可使用。(Nuclear adaptive filtering algorithm krls matlab program. Klms algorithm has inflicted function, load can be used.)

用SIFT算法实现了刚性和非刚性图像的配准 并且效果非常理想 SIFT的特征点的提取 描述 和匹配的算法有注释(Nonrigid Registration Using Free-Form Deformation. )

HOG特征提取，以通过测试。希望对大家能有所帮助。(HOG feature extraction, in order to pass the test. I hope we can help.)

实现图像颜色识别分块实现图像颜色识别分块(Block of image color recognition)

类似PChunter的内核工具。本工具是应用层的源码。适合内核新手(Similar PChunter core tools. This tool is the source application layer. Suitable for novice kernel)

车流量检测,车流量检测,车流量检测,车流量检测,(traffic flow,traffic flow,traffic flow,traffic flow)