Python实现PS滤镜的旋转模糊功能示例

Python  /  管理员 发布于 7年前   139

本文实例讲述了Python实现PS滤镜的旋转模糊功能。分享给大家供大家参考，具体如下：

这里用 Python 实现 PS 滤镜中的旋转模糊，具体的算法原理和效果可以参考附录相关介绍。Python代码如下：

from skimage import img_as_floatimport matplotlib.pyplot as pltfrom skimage import ioimport numpy as npimport numpy.matlibfile_name='D:/Visual Effects/PS Algorithm/4.jpg'img=io.imread(file_name)img = img_as_float(img)img_out = img.copy()row, col, channel = img.shapexx = np.arange (col)yy = np.arange (row)x_mask = numpy.matlib.repmat (xx, row, 1)y_mask = numpy.matlib.repmat (yy, col, 1)y_mask = np.transpose(y_mask)center_y = (row -1) / 2.0center_x = (col -1) / 2.0R = np.sqrt((x_mask - center_x) **2 + (y_mask - center_y) ** 2)angle = np.arctan2(y_mask - center_y , x_mask - center_x)Num = 20arr = ( np.arange(Num) + 1 ) / 100.0for i in range (row):  for j in range (col):    T_angle = angle[i, j] + arr    new_x = R[i, j] * np.cos(T_angle) + center_x    new_y = R[i, j] * np.sin(T_angle) + center_y    int_x = new_x.astype(int)    int_y = new_y.astype(int)    int_x[int_x > col-1] = col - 1    int_x[int_x < 0] = 0    int_y[int_y < 0] = 0    int_y[int_y > row -1] = row -1    img_out[i,j,0] = img[int_y, int_x, 0].sum()/Num    img_out[i,j,1] = img[int_y, int_x, 1].sum()/Num    img_out[i,j,2] = img[int_y, int_x, 2].sum()/Numplt.figure(1)plt.imshow(img)plt.axis('off')plt.figure(2)plt.imshow(img_out)plt.axis('off')plt.show()

附：PS 滤镜――旋转模糊

这里给出灰度图像的模糊算法，彩色图像只要分别对三个通道做模糊即可。

%% spin blur% 旋转模糊clc;clear all;close all;I=imread('4.jpg');I=double(I);% % % I_new=I;% % % for kk=1:3% % %   I_new(:,:,kk)=Spin_blur_Fun(I(:,:,kk), 30, 30);% % % end% % % imshow(I_new/255)Image=I;Image=0.2989 * I(:,:,1) + 0.5870 * I(:,:,2) + 0.1140 * I(:,:,3);[row, col]=size(Image);Image_new=Image;Center_X=(col+1)/2;Center_Y=(row+1)/2;validPoint=1;angle=5;radian=angle*pi/180;radian2=radian*radian;Num=30;Num2=Num*Num;for i=1:row  for j=1:col    validPoint=1;    x0=j-Center_X;    y0=Center_Y-i;    x1=x0;    y1=y0;    Sum_Pixel=Image(i,j);    for k=1:Num      x0=x1;      y0=y1;      %%% 逆时针      % x1=x0-radian*y0/Num-radian2*x0/Num2;      % y1=y0+radian*x0/Num-radian2*y0/Num2;      %%% 顺时针      x1=x0+radian*y0/Num-radian2*x0/Num2;      y1=y0-radian*x0/Num-radian2*y0/Num2;      x=floor(x1+Center_X);      y=floor(Center_Y-y1);      if(x>1 && x<col && y>1 && y<row)        validPoint=validPoint+1;        Sum_Pixel=Sum_Pixel+Image(y,x);      end    end    Image_new(i,j)=Sum_Pixel/validPoint;  endend imshow(Image_new/255);

原图

效果图

效果图

更多关于Python相关内容感兴趣的读者可查看本站专题：《Python图片操作技巧总结》、《Python数据结构与算法教程》、《Python Socket编程技巧总结》、《Python函数使用技巧总结》、《Python字符串操作技巧汇总》、《Python入门与进阶经典教程》及《Python文件与目录操作技巧汇总》

希望本文所述对大家Python程序设计有所帮助。