''' Coherence-enhancing filtering example inspired by Joachim Weickert "Coherence-Enhancing Shock Filters" http://www.mia.uni-saarland.de/Publications/weickert-dagm03.pdf ''' import numpy as np import cv2, cv def coherence_filter(img, sigma = 11, str_sigma = 11, blend = 0.5, iter_n = 4): h, w = img.shape[:2] for i in xrange(iter_n): print i, gray = cv2.cvtColor(img, cv.CV_BGR2GRAY) eigen = cv2.cornerEigenValsAndVecs(gray, str_sigma, 3) eigen = eigen.reshape(h, w, 3, 2) # [[e1, e2], v1, v2] x, y = eigen[:,:,1,0], eigen[:,:,1,1] gxx = cv2.Sobel(gray, cv2.CV_32F, 2, 0, ksize=sigma) gxy = cv2.Sobel(gray, cv2.CV_32F, 1, 1, ksize=sigma) gyy = cv2.Sobel(gray, cv2.CV_32F, 0, 2, ksize=sigma) gvv = x*x*gxx + 2*x*y*gxy + y*y*gyy m = gvv < 0 ero = cv2.erode(img, None) dil = cv2.dilate(img, None) img1 = ero img1[m] = dil[m] img = np.uint8(img*(1.0 - blend) + img1*blend) print 'done' return img if __name__ == '__main__': import sys try: fn = sys.argv[1] except: fn = '../cpp/baboon.jpg' src = cv2.imread(fn) def nothing(*argv): pass def update(): sigma = cv2.getTrackbarPos('sigma', 'control')*2+1 str_sigma = cv2.getTrackbarPos('str_sigma', 'control')*2+1 blend = cv2.getTrackbarPos('blend', 'control') / 10.0 print 'sigma: %d str_sigma: %d blend_coef: %f' % (sigma, str_sigma, blend) dst = coherence_filter(src, sigma=sigma, str_sigma = str_sigma, blend = blend) cv2.imshow('dst', dst) cv2.namedWindow('control', 0) cv2.createTrackbar('sigma', 'control', 9, 15, nothing) cv2.createTrackbar('blend', 'control', 7, 10, nothing) cv2.createTrackbar('str_sigma', 'control', 9, 15, nothing) print 'Press SPACE to update the image\n' cv2.imshow('src', src) update() while True: ch = cv2.waitKey() if ch == ord(' '): update() if ch == 27: break