cv2.imwrite("ldr-Drago.jpg", ldrDrago * 255)
print("saved ldr-Drago.jpg")
#
# Tonemap using Durand's method obtain 24-bit color image
print("Tonemaping using Durand's method ... ")
tonemapDurand = cv2.createTonemapDurand(1.5, 4, 1.0, 1, 1)
ldrDurand = tonemapDurand.process(hdrDebevec)
ldrDurand = 3 * ldrDurand
cv2.imwrite("ldr-Durand.jpg", ldrDurand * 255)
print("saved ldr-Durand.jpg")
#
# Tonemap using Reinhard's method to obtain 24-bit color image
print("Tonemaping using Reinhard's method ... ")
tonemapReinhard = cv2.createTonemapReinhard(1.5, 0, 0, 0)
ldrReinhard = tonemapReinhard.process(hdrDebevec)
cv2.imwrite("ldr-Reinhard.jpg", ldrReinhard * 255)
print("saved ldr-Reinhard.jpg")
# Tonemap using Mantiuk's method to obtain 24-bit color image
print("Tonemaping using Mantiuk's method ... ")
tonemapMantiuk = cv2.createTonemapMantiuk(2.2, 0.85, 1.2)
ldrMantiuk = tonemapMantiuk.process(hdrDebevec)
ldrMantiuk = 3 * ldrMantiuk
# cv2.imwrite("ldr-Mantiuk.jpg", ldrMantiuk * 255)
# print("saved ldr-Mantiuk.jpg")
plt.figure()
plt.imshow(ldrMantiuk)
plt.show()
def mainfunction():
img1 = cv2.imread('processed_exposure1.tiff')
img1 = cv2.resize(img1, None, fx=0.25, fy=0.25)
img1 = img1.astype(np.float16)
img1 = img1 / 65535
img2 = cv2.imread('processed_exposure2.tiff')
img2 = cv2.resize(img2, None, fx=0.25, fy=0.25)
img2 = img2.astype(np.float16)
img2 = img2 / 65535
img3 = cv2.imread('processed_exposure3.tiff')
img3 = cv2.resize(img3, None, fx=0.25, fy=0.25)
img3 = img3.astype(np.float16)
img3 = img3 / 65535
img4 = cv2.imread('processed_exposure4.tiff')
img4 = cv2.resize(img4, None, fx=0.25, fy=0.25)
img4 = img4.astype(np.float16)
img4 = img4 / 65535
img5 = cv2.imread('processed_exposure5.tiff')
img5 = cv2.resize(img5, None, fx=0.25, fy=0.25)
img5 = img5.astype(np.float16)
img5 = img5 / 65535
img6 = cv2.imread('processed_exposure6.tiff')
img6 = cv2.resize(img6, None, fx=0.25, fy=0.25)
img6 = img6.astype(np.float16)
img6 = img6 / 65535
img7 = cv2.imread('processed_exposure7.tiff')
img7 = cv2.resize(img7, None, fx=0.25, fy=0.25)
img7 = img7.astype(np.float16)
img7 = img7 / 65535
img8 = cv2.imread('processed_exposure8.tiff')
img8 = cv2.resize(img8, None, fx=0.25, fy=0.25)
img8 = img8.astype(np.float16)
img8 = img8 / 65535
img9 = cv2.imread('processed_exposure9.tiff')
img9 = cv2.resize(img9, None, fx=0.25, fy=0.25)
img9 = img9.astype(np.float16)
img9 = img9 / 65535
img10 = cv2.imread('processed_exposure10.tiff')
img10 = cv2.resize(img10, None, fx=0.25, fy=0.25)
img10 = img10.astype(np.float16)
img10 = img10 / 65535
img11 = cv2.imread('processed_exposure11.tiff')
img11 = cv2.resize(img11, None, fx=0.25, fy=0.25)
img11 = img11.astype(np.float16)
img11 = img11 / 65535
img12 = cv2.imread('processed_exposure12.tiff')
img12 = cv2.resize(img12, None, fx=0.25, fy=0.25)
img12 = img12.astype(np.float16)
img12 = img12 / 65535
img13 = cv2.imread('processed_exposure13.tiff')
img13 = cv2.resize(img13, None, fx=0.25, fy=0.25)
img13 = img13.astype(np.float16)
img13 = img13 / 65535
img14 = cv2.imread('processed_exposure14.tiff')
img14 = cv2.resize(img14, None, fx=0.25, fy=0.25)
img14 = img14.astype(np.float16)
img14 = img14 / 65535
img15 = cv2.imread('processed_exposure15.tiff')
img15 = cv2.resize(img15, None, fx=0.25, fy=0.25)
img15 = img15.astype(np.float16)
img15 = img15 / 65535
img16 = cv2.imread('processed_exposure16.tiff')
img16 = cv2.resize(img16, None, fx=0.25, fy=0.25)
img16 = img16.astype(np.float16)
img16 = img16 / 65535
listofimages = [
img1, img2, img3, img4, img5, img6, img7, img8, img9, img10, img11,
img12, img13, img14, img15, img16
]
#=np.zeros([4016,6016,3])
I = np.zeros([1004, 1504, 3])
#I=np.zeros([1000,1000,3])
for i in range(0, 1004): #g1.shape[0])
for j in range(0, 1504): #img1.shape[1]
for c in range(0, 3):
s = 0
s1 = 0
for k in range(0, 16):
x = listofimages[k] #Reteiving the image from the list
t = time(k + 1) #Calculating thr time
value = x[i, j, c] #Storing the value
weightk = weight(x[i, j, c]) #Calculating weight
s = s + (weightk * value) / t
s1 = s1 + weightk
I[i, j, c] = s / s1
print(I[i, j, c], i, j, c)
#Performing Photographic tone mapping
tonemap = np.divide(I, (1 + I)) #Using the formula IHDR/1+IHDR
tonemap8 = (tonemap / np.max(tonemap) * 255).astype(
np.uint8) #Performing the conversion to uint8
cv2.imwrite('Photographic_tonemapping.png',
tonemap8) #Displaying the image
#Performing tonemapping using the opencv functions
I = I.astype(np.float32) #Change to float32
tonemapMantiuk = cv2.createTonemapMantiuk(
2.2, 0.7, -0.1) #Creating object of the tonemap class
ldrMantiuk = tonemapMantiuk.process(
I) #Performing the process of the mapping
cv2.imwrite('opencv_tonemapping2.png', ldrMantiuk)
print("Tonemaping using Drago's method ... ")
tonemapDrago = cv2.createTonemapDrago(1.0, 0.7)
ldrDrago = tonemapDrago.process(hdrDebevec)
ldrDrago = 3 * ldrDrago
cv2.imwrite("ldr-Drago.jpg", ldrDrago * 255)
print("saved ldr-Drago.jpg")
# Tonemap using Durand's method obtain 24-bit color image
print("Tonemaping using Durand's method ... ")
tonemapDurand = cv2.createTonemapDurand(1.5,4,1.0,1,1)
ldrDurand = tonemapDurand.process(hdrDebevec)
ldrDurand = 3 * ldrDurand
cv2.imwrite("ldr-Durand.jpg", ldrDurand * 255)
print("saved ldr-Durand.jpg")
# Tonemap using Reinhard's method to obtain 24-bit color image
print("Tonemaping using Reinhard's method ... ")
tonemapReinhard = cv2.createTonemapReinhard(1.5, 0,0,0)
ldrReinhard = tonemapReinhard.process(hdrDebevec)
cv2.imwrite("ldr-Reinhard.jpg", ldrReinhard * 255)
print("saved ldr-Reinhard.jpg")
# Tonemap using Mantiuk's method to obtain 24-bit color image
print("Tonemaping using Mantiuk's method ... ")
tonemapMantiuk = cv2.createTonemapMantiuk(2.2,0.85, 1.2)
ldrMantiuk = tonemapMantiuk.process(hdrDebevec)
ldrMantiuk = 3 * ldrMantiuk
cv2.imwrite("ldr-Mantiuk.jpg", ldrMantiuk * 255)
print("saved ldr-Mantiuk.jpg")
def tone_mapping_Mantiuk(hdrDebevec):
tonemapMantiuk = cv2.createTonemapMantiuk(2.2, 0.85, 1.2)
ldrMantiuk = tonemapMantiuk.process(hdrDebevec)
ldrMantiuk = 3 * ldrMantiuk
return ldrMantiuk * 255