本文实例讲述了Python实现PS图像调整颜色梯度效果。分享给大家供大家参考，具体如下：
这里用 Python 实现 PS 中的色彩图，可以看到颜色的各种渐变，具体的效果可以参考附录说明
和之前的程序相比，这里利用矩阵的运算替代了 for 循环，提升了运行的效率。
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import numpy as np
import matplotlib.pyplot as plt
from skimage import io
import numpy.matlib
from skimage import img_as_float
file_name='D:/Visual Effects/PS Algorithm/4.jpg';
img=io.imread(file_name)
img = img_as_float(img)
row, col, channel = img.shape
rNW = 0.5
rNE = 1.0
rSW = 1.0
rSE = 0.0
gNW = 0.0
gNE = 0.5
gSW = 0.0
gSE = 1.0
bNW = 1.0
bNE = 0.0
bSW = 1.0
bSE = 0.0
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)
fx = x_mask * 1.0 / col
fy = y_mask * 1.0 / row
p = rNW + (rNE - rNW) * fx
q = rSW + (rSE - rSW) * fx
r = ( p + (q - p) * fy )
r[r<0] = 0
r[r>1] =1
p = gNW + (gNE - gNW) * fx
q = gSW + (gSE - gSW) * fx
g = ( p + (q - p) * fy )
g[g<0] = 0
g[g>1] =1
p = bNW + (bNE - bNW) * fx
q = bSW + (bSE - bSW) * fx
b = ( p + (q - p) * fy )
b[b<0] = 0.0
b[b>1] = 1.0
img[:, :, 0] = r
img[:, :, 1] = g
img[:, :, 2] = b
plt.figure(1)
plt.imshow(img)
plt.axis('off');
plt.show();
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附录：PS 色调— —颜色梯度
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clc;
clear all;
close all;
addpath('E:\PhotoShop Algortihm\Image Processing\PS Algorithm');
I=imread('4.jpg');
Image=double(I)/255;
[height, width, depth]=size(Image);
rNW=1.0; gNW=0.0; bNW=0.0;
rNE=1.0; gNE=1.0; bNE=0.0;
rSW=0.0; gSW=0; bSW=1.0;
rSE=0.0; gSE=1.0; bSE=0.0;
Img_new=Image;
for ii=1:height
for jj=1:width
fx = jj / width;
fy = ii / height;
p = rNW + (rNE - rNW) * fx;
q = rSW + (rSE - rSW) * fx;
r = ( p + (q - p) * fy );
r = min(max(r, 0), 1);
p = gNW + (gNE - gNW) * fx;
q = gSW + (gSE - gSW) * fx;
g = ( p + (q - p) * fy );
g = min(max(g, 0) ,1);
p = bNW + (bNE - bNW) * fx;
q = bSW + (bSE - bSW) * fx;
b = ( p + (q - p) * fy );
b = min(max(b, 0), 1);
Img_new(ii, jj, 1)=r;
Img_new(ii, jj, 2)=g;
Img_new(ii, jj, 3)=b;
end
end
imshow(Img_new);
imwrite(Img_new, 'out.jpg');
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参考来源：http://www.jhlabs.com/index.html
本例Python运行效果图：
原图：
运行效果：
希望本文所述对大家Python程序设计有所帮助。
原文链接：http://blog.csdn.net/matrix_space/article/details/72302964