image-processing

这是一个简单的掌纹识别系统，运用了PCA算法，可以做到较快的运算。(This is a simple palmprint recognition system that uses the PCA algorithm to achieve faster calculations.)

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.)

说明：  一些快速实现图像模糊增强的的demo，matlab源码。已经测试通过。(Some image blurring rapidly enhanced the demo, matlab source. Have the test.)

这是一个基于vc++语言下读取像素点灰度值(write highhui of a photo!)

计算交通格子模型的能量耗散和污染排放，包括 一氧化碳，一氧化氮，和其他污染物的排放，并在一图表中进行比较(Traffic grid calculation model of energy dissipation and pollution emissions, including carbon monoxide, nitrogen oxides, and other pollutants, and comparing in a chart)

基于梯度相似度的图像质量评价方法，发表在2012年TIP国际期刊上(A. Liu, W. Lin, M. Narwaria, “Image Quality Assessment Based on Gradient Similarity,” IEEE Transactions on Image Processing, vol. 21(4), pp. 1500-1512, 2012.)

说明：  掌纹roi提取 掌纹图像处理 图像分割(Extraction of palmprint roi)

读取RAW格式文件，将其转换为BMP格式文件并存储(raw 2 bmp file format convert)

图像 自动 标注 通过分析 训练集 ，学习 图像 和标注词 之间的关系，得出 之间的关系，得出 一些规则， 然后使用这些规则 自动 推导出 图像 最适合的标注词 ，这些标注词代表了图像的 ，这些标注词代表了图像的 高层 语义信息 。(Automatic image annotation by analyzing the training set, learning image and mark the relationship between words, the relationship between the draw, draw some rules, and then use these rules to automatically derive the most suitable image annotation words, these words represent the image annotation , these words represent the image annotation level semantic information.)

利用极大似然估计进行盲反卷积复原，通过多帧图像约束，效果较好(Use of maximum likelihood estimates for blind deconvolution restoration by the multi-frame image constraint, the better)