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:

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。

%% 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

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