geomosaic

利用非参数贝叶斯字典学习模型进行图像稀疏表示(use non-parametric-bayesian-dictionary-learning-for-sparse-image-representations)

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.)

本程序实现了两种误差扩散算法，分别用Sierra扩散滤波器和stenenson扩散滤波器，实现了比Floy_stein更好的误差扩散半色调效果。(This procedure implements two error diffusion algorithm, respectively Sierra diffusion filters and stenenson diffusion filter, to achieve better than Floy_stein error diffusion halftone effects.)

五线谱的简单识别 识别出点的位置 需要数据灰度图(we can know how to know music)

矩阵卷积的几种版本：conv函数，矩阵乘法形式，纯矩阵乘法形式(Several versions of matrix convolution: convolutional vision, matrix vision, only-matrix vision)

基于四阶偏微分方程的图像去噪算法，能够有效去除阶梯效应，自己编的程序(image denoising using fourth-order PDEs)

用均值滤波、中值滤波、维纳滤波法给加高斯噪声的图像去噪(Using the mean filter, median filter, Wiener filter to add the Gaussian noise image denoising)

乳腺X线图像增强质量评价的ＭＡＴＬＡＢ程序，这里使用对比度和ＤＳＭ两种评价方法对乳腺Ｘ线图像增强方法的优劣做一个客观的评价。(Breast X-ray image enhancement the quality assessment of the MATLAB program, where the use of contrast and DSM two evaluation methods to make an objective assessment of the pros and cons of breast X-ray image enhancement method.)

实现了一个基于颜色、纹理、形状综合特征的MatlabGUI图像检索系统。(Bulit an image retrieval system based on which combines these three features and realizes user-defined weights.)

说明：  用于处理超声波相控阵C扫描的数据文件和图片处理，采用的是Matlab语言(the code of Matlab is used to process the data file and picture of ultrasonic phased array C scan)