mirror of
https://github.com/opencv/opencv.git
synced 2024-11-30 06:10:02 +08:00
131 lines
3.7 KiB
Python
Executable File
131 lines
3.7 KiB
Python
Executable File
#!/usr/bin/env python
|
|
|
|
'''
|
|
Wiener deconvolution.
|
|
|
|
Sample shows how DFT can be used to perform Weiner deconvolution [1]
|
|
of an image with user-defined point spread function (PSF)
|
|
|
|
Usage:
|
|
deconvolution.py [--circle]
|
|
[--angle <degrees>]
|
|
[--d <diameter>]
|
|
[--snr <signal/noise ratio in db>]
|
|
[<input image>]
|
|
|
|
Use sliders to adjust PSF paramitiers.
|
|
Keys:
|
|
SPACE - switch btw linear/cirular PSF
|
|
ESC - exit
|
|
|
|
Examples:
|
|
deconvolution.py --angle 135 --d 22 ../data/licenseplate_motion.jpg
|
|
(image source: http://www.topazlabs.com/infocus/_images/licenseplate_compare.jpg)
|
|
|
|
deconvolution.py --angle 86 --d 31 ../data/text_motion.jpg
|
|
deconvolution.py --circle --d 19 ../data/text_defocus.jpg
|
|
(image source: compact digital photo camera, no artificial distortion)
|
|
|
|
|
|
[1] http://en.wikipedia.org/wiki/Wiener_deconvolution
|
|
'''
|
|
|
|
# Python 2/3 compatibility
|
|
from __future__ import print_function
|
|
|
|
import numpy as np
|
|
import cv2
|
|
|
|
# local module
|
|
from common import nothing
|
|
|
|
|
|
def blur_edge(img, d=31):
|
|
h, w = img.shape[:2]
|
|
img_pad = cv2.copyMakeBorder(img, d, d, d, d, cv2.BORDER_WRAP)
|
|
img_blur = cv2.GaussianBlur(img_pad, (2*d+1, 2*d+1), -1)[d:-d,d:-d]
|
|
y, x = np.indices((h, w))
|
|
dist = np.dstack([x, w-x-1, y, h-y-1]).min(-1)
|
|
w = np.minimum(np.float32(dist)/d, 1.0)
|
|
return img*w + img_blur*(1-w)
|
|
|
|
def motion_kernel(angle, d, sz=65):
|
|
kern = np.ones((1, d), np.float32)
|
|
c, s = np.cos(angle), np.sin(angle)
|
|
A = np.float32([[c, -s, 0], [s, c, 0]])
|
|
sz2 = sz // 2
|
|
A[:,2] = (sz2, sz2) - np.dot(A[:,:2], ((d-1)*0.5, 0))
|
|
kern = cv2.warpAffine(kern, A, (sz, sz), flags=cv2.INTER_CUBIC)
|
|
return kern
|
|
|
|
def defocus_kernel(d, sz=65):
|
|
kern = np.zeros((sz, sz), np.uint8)
|
|
cv2.circle(kern, (sz, sz), d, 255, -1, cv2.LINE_AA, shift=1)
|
|
kern = np.float32(kern) / 255.0
|
|
return kern
|
|
|
|
|
|
if __name__ == '__main__':
|
|
print(__doc__)
|
|
import sys, getopt
|
|
opts, args = getopt.getopt(sys.argv[1:], '', ['circle', 'angle=', 'd=', 'snr='])
|
|
opts = dict(opts)
|
|
try:
|
|
fn = args[0]
|
|
except:
|
|
fn = '../data/licenseplate_motion.jpg'
|
|
|
|
win = 'deconvolution'
|
|
|
|
img = cv2.imread(fn, 0)
|
|
if img is None:
|
|
print('Failed to load fn1:', fn1)
|
|
sys.exit(1)
|
|
|
|
img = np.float32(img)/255.0
|
|
cv2.imshow('input', img)
|
|
|
|
img = blur_edge(img)
|
|
IMG = cv2.dft(img, flags=cv2.DFT_COMPLEX_OUTPUT)
|
|
|
|
defocus = '--circle' in opts
|
|
|
|
def update(_):
|
|
ang = np.deg2rad( cv2.getTrackbarPos('angle', win) )
|
|
d = cv2.getTrackbarPos('d', win)
|
|
noise = 10**(-0.1*cv2.getTrackbarPos('SNR (db)', win))
|
|
|
|
if defocus:
|
|
psf = defocus_kernel(d)
|
|
else:
|
|
psf = motion_kernel(ang, d)
|
|
cv2.imshow('psf', psf)
|
|
|
|
psf /= psf.sum()
|
|
psf_pad = np.zeros_like(img)
|
|
kh, kw = psf.shape
|
|
psf_pad[:kh, :kw] = psf
|
|
PSF = cv2.dft(psf_pad, flags=cv2.DFT_COMPLEX_OUTPUT, nonzeroRows = kh)
|
|
PSF2 = (PSF**2).sum(-1)
|
|
iPSF = PSF / (PSF2 + noise)[...,np.newaxis]
|
|
RES = cv2.mulSpectrums(IMG, iPSF, 0)
|
|
res = cv2.idft(RES, flags=cv2.DFT_SCALE | cv2.DFT_REAL_OUTPUT )
|
|
res = np.roll(res, -kh//2, 0)
|
|
res = np.roll(res, -kw//2, 1)
|
|
cv2.imshow(win, res)
|
|
|
|
cv2.namedWindow(win)
|
|
cv2.namedWindow('psf', 0)
|
|
cv2.createTrackbar('angle', win, int(opts.get('--angle', 135)), 180, update)
|
|
cv2.createTrackbar('d', win, int(opts.get('--d', 22)), 50, update)
|
|
cv2.createTrackbar('SNR (db)', win, int(opts.get('--snr', 25)), 50, update)
|
|
update(None)
|
|
|
|
while True:
|
|
ch = cv2.waitKey() & 0xFF
|
|
if ch == 27:
|
|
break
|
|
if ch == ord(' '):
|
|
defocus = not defocus
|
|
update(None)
|