我需要基于正常图片合成许多具有不同固有矩阵的FishEye图像。我正在遵循此paper中提到的方法。
理想情况下,如果算法正确,理想的鱼眼效果应如下所示:
。
但是当我使用算法转换图片时
看起来像这样
所以下面是我的代码流程: 1.首先,我使用cv2读取原始图像
def read_img(image):
img = ndimage.imread(image) #this would return a 4-d array: [R,G,B,255]
img_shape = img.shape
print(img_shape)
#get the pixel coordinate
w = img_shape[1] #the width
# print(w)
h= img_shape[0] #the height
# print(h)
uv_coord = []
for u in range(w):
for v in range(h):
uv_coord.append([float(u),float(v)]) #this records the coord in the fashion of [x1,y1],[x1, y2], [x1, y3]....
return np.array(uv_coord)
然后,基于纸张:
r(θ)=k1θ+k2θ^ 3 +k3θ^ 5 +k4θ^ 7,(1) 其中Ks是失真系数
鉴于针孔投影图像中的像素坐标(x,y),鱼眼中相应的图像坐标(x',y')可以计算为:
x'= r(θ)cos(ϕ),y'= r(θ)sin(ϕ),(2)
其中 ϕ = arctan((y-y0)/(x-x0)) ,而(x0,y0)是坐标中主点的坐标针孔投影图像。
然后将图像坐标(x',y')转换为像素坐标(xf,yf):(xf,yf): * xf = mu * x'+ u0,yf = mv * y'+ v0,* (3)
其中(u0,v0)是鱼眼中主要点的坐标,而mu,mv表示水平和垂直方向上每单位距离的像素数。因此,我猜想 本征矩阵 中只有[fx,fy]和u0 v0是[cx,cy]。
def add_distortion(sourceUV, dmatrix,Kmatrix):
'''This function is programmed to remove the pixel of the given original image coords
input arguments:
dmatrix -- the intrinsic matrix [k1,k2,k3,k4] for tweaking purposes
Kmatrix -- [fx, fy, cx, cy, s]'''
u = sourceUV[:,0] #width in x
v = sourceUV[:,1] #height in y
rho = np.sqrt(u**2 + v**2)
#get theta
theta = np.arctan(rho,np.full_like(u,1))
# rho_mat = np.array([rho, rho**3, rho**5, rho**7])
rho_mat = np.array([theta,theta**3, theta**5, theta**7])
#get the: rho(theta) = k1*theta + k2*theta**3 + k3*theta**5 + k4*theta**7
rho_d = dmatrix@rho_mat
#get phi
phi = np.arctan2((v - Kmatrix[3]), (u - Kmatrix[2]))
xd = rho_d * np.cos(phi)
yd = rho_d * np.sin(phi)
#converting the coords from image plane back to pixel coords
ud = Kmatrix[0] * (xd + Kmatrix[4] * yd) + Kmatrix[2]
vd = Kmatrix[1] * yd + Kmatrix[3]
return np.column_stack((ud,vd))
然后在获得变形的坐标之后,我以这种方式执行运动像素,我认为问题可能是:
def main():
image_name = "original.png"
img = cv2.imread(image_name)
img = cv2.cvtColor(img, cv2.COLOR_RGB2BGR) #the cv2 read the image as BGR
w = img.shape[1]
h = img.shape[0]
uv_coord = read_img(image_name)
#for adding distortion
dmatrix = [-0.391942708316175,0.012746418822063 ,-0.001374061848026 ,0.005349692659231]
#the Intrinsic matrix of the original picture's
Kmatrix = np.array([9.842439e+02,9.808141e+02 , 1392/2, 2.331966e+02, 0.000000e+00])
# Kmatrix = np.array([2234.23470710156 ,2223.78349134123, 947.511596277837, 647.103139639432,-3.20443253476976]) #the distorted intrinsics
uv = add_distortion(uv_coord,dmatrix,Kmatrix)
i = 0
dstimg = np.zeros_like(img)
for x in range(w): #tthe coo
for y in range(h):
if i > (512 * 1392 -1):
break
xu = uv[i][0] #x, y1, y2, y3
yu = uv[i][1]
i +=1
# if new pixel is in bounds copy from source pixel to destination pixel
if 0 <= xu and xu < img.shape[1] and 0 <= yu and yu < img.shape[0]:
dstimg[int(yu)][int(xu)] = img[int(y)][int(x)]
img = Image.fromarray(dstimg, 'RGB')
img.save('my.png')
img.show()
但是,此代码无法按照我想要的方式执行。你们能帮我调试吗?我花了3天,但仍然看不到任何问题。谢谢!