Python实现PS滤镜的旋转模糊功能示例

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：

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from skimage import img_as_float import matplotlib.pyplot as plt from skimage import io import numpy as np import numpy.matlib file_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.shape xx = 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) / 2.0 center_x = (col -1) / 2.0 R = np.sqrt((x_mask - center_x) **2 + (y_mask - center_y) ** 2) angle = np.arctan2(y_mask - center_y , x_mask - center_x) Num = 20 arr = ( np.arange(Num) + 1 ) / 100.0 for 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()/Num plt.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。

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%% 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;   end end  imshow(Image_new/255);

原图

效果图

效果图