图像的莫尔纹效应

最近看到二维傅立叶图像变换，其中提到了莫尔纹。生活当中莫尔纹很容易见到，就像用python显示出来。于是写了一段代码。

import cv2 as cv

import numpy as np

import matplotlib.pyplot as pyplot

img1=np.zeros([200,200],np.uint8)

[w,h] = img1.shape

for i in range(0,w):
    for j in range(0,h):
        if int(j / 5) % 2 == 0:
            img1[i,j] = 255

pyplot.imshow(img1,cmap='gray')

<matplotlib.image.AxesImage at 0x13727f310>

[外链图片转存失败,源站可能有防盗链机制,建议将图片保存下来直接上传(img-yZzevzbJ-1590672698492)(output_6_1.png)]

img2=np.zeros([200,200],np.uint8)

for i in range(0,w):
    for j in range(0,h):
        if int(j / 7) % 2 == 0:
            img2[i,j] = 255

pyplot.imshow(img2,cmap='gray')

<matplotlib.image.AxesImage at 0x10a938ed0>

[外链图片转存失败,源站可能有防盗链机制,建议将图片保存下来直接上传(img-ZdQ1Ebjx-1590672698493)(output_9_1.png)]

imgRotateM = cv.getRotationMatrix2D((100,100),30,0.7)

imgRotate = cv.warpAffine(img2,imgRotateM,(200,200))

pyplot.imshow(imgRotate,cmap='gray')

<matplotlib.image.AxesImage at 0x10aa29510>

[外链图片转存失败,源站可能有防盗链机制,建议将图片保存下来直接上传(img-TMCxg7fu-1590672698494)(output_12_1.png)]

imgMerge = 0.5 * img1 + 0.5 * imgRotate

pyplot.imshow(imgMerge,cmap='gray')

<matplotlib.image.AxesImage at 0x1375b30d0>

[外链图片转存失败,源站可能有防盗链机制,建议将图片保存下来直接上传(img-xTACLmVw-1590672698494)(output_14_1.png)]

去github
https://github.com/LuckilyHaveYou/LearningCode/blob/master/图像的莫尔纹效应.ipynb