Modeling a Bayer detector#

import lentil
import numpy as np
import matplotlib.pyplot as plt
import scipy.signal

gaussian = scipy.signal.windows.gaussian(250, 25)
gaussian = gaussian[25:-25]
qe_wave = np.arange(350, 750)*1e-9

qe_red = np.zeros(qe_wave.size)
qe_green = np.zeros(qe_wave.size)
qe_blue = np.zeros(qe_wave.size)

qe_blue[10:210] = gaussian
qe_green[90:290] = gaussian
qe_red[170:370] = gaussian


plt.plot(qe_wave, qe_blue, 'b', label='Blue')
plt.plot(qe_wave, qe_green, 'g', label='Green')
plt.plot(qe_wave, qe_red, 'r', label='Red')
plt.legend()
plt.title('Quantum Efficiency')
plt.xlabel('Wavelength [nm]')
plt.grid()
../_images/bayer-1.png 
amp = lentil.circle((256,256), 120)
amp -= lentil.circle(shape=(256,256), radius=40)
for angle in (0, 90, 180, 270):
    amp *= lentil.spider((256,256), 2, angle)

opd = lentil.zernike(amp, 4)*1e-6

psf = []

p = lentil.Pupil(amplitude=amp, opd=opd, focal_length=10, pixelscale=1/240)

for wave in np.arange(350, 750):
    w = lentil.Wavefront(wave*1e-9)
    w *= p
    w = lentil.propagate_dft(w, pixelscale=5e-6, shape=(64, 64),
                            oversample=2)
    psf.append(w.intensity)

psf = np.asarray(psf)
psf = lentil.rebin(psf, 2)

psf_flat = np.sum(psf, axis=0)

fig, ax = plt.subplots(figsize=(2.5,2.5))
ax.imshow(psf_flat, cmap='inferno')
ax.set_title('Broadband PSF')
plt.axis('off')
../_images/bayer-2.png 
img = lentil.detector.collect_charge_bayer(psf, qe_wave, qe_red, qe_green,
                                        qe_blue, 'BGGR')

red_kernel = np.array([[0,0],[0,1]])
green_kernel = np.array([[0,1],[1,0]])
blue_kernel = np.array([[1,0],[0,0]])

red_mosaic = np.tile(red_kernel, (img.shape[0]//2, img.shape[1]//2))
green_mosaic = np.tile(green_kernel, (img.shape[0]//2, img.shape[1]//2))
blue_mosaic = np.tile(blue_kernel, (img.shape[0]//2, img.shape[1]//2))

img = img/np.max(img)

r = red_mosaic * img
g = green_mosaic * img
b = blue_mosaic * img

fig, ax = plt.subplots(nrows=1, ncols=4, figsize=(7,3))

ax[0].imshow(r, cmap='gray')
ax[0].set_title('Red')
ax[0].axis('off')

ax[1].imshow(g, cmap='gray')
ax[1].set_title('Green')
ax[1].axis('off')

ax[2].imshow(b, cmap='gray')
ax[2].set_title('Blue')
ax[2].axis('off')

ax[3].imshow(img, cmap='gray')
ax[3].set_title('Full Bayer image')
ax[3].axis('off')
../_images/bayer-3.png