def HSVStretching(sceneRadiance):
height = len(sceneRadiance)
width = len(sceneRadiance[0])
img_hsv = rgb2hsv(sceneRadiance)
h, s, v = cv2.split(img_hsv)
img_s_stretching = global_stretching(s, height, width)
# print('np.min(img_s_stretching)',np.min(img_s_stretching))
# print('np.max(img_s_stretching)',np.max(img_s_stretching))
# print('np.mean(img_s_stretching)',np.mean(img_s_stretching))
img_v_stretching = global_stretching(v, height, width)
# print('np.min(img_v_stretching)', np.min(img_v_stretching))
# print('np.max(img_v_stretching)', np.max(img_v_stretching))
# print('np.mean(img_v_stretching)', np.mean(img_v_stretching))
# img_L_sHretching = global_Stretching.global_stretching(L, height, width)
# img_a_stretching = global_stretching_ab.global_Stretching_ab(a, height, width)
# img_b_stretching = global_stretching_ab.global_Stretching_ab(b, height, width)
labArray = np.zeros((height, width, 3), 'float64')
labArray[:, :, 0] = h
labArray[:, :, 1] = img_s_stretching
labArray[:, :, 2] = img_v_stretching
img_rgb = hsv2rgb(labArray) * 255
# img_rgb = np.clip(img_rgb, 0, 255)
return img_rgb
def HSVStretching(sceneRadiance):
sceneRadiance = np.uint8(sceneRadiance)
height = len(sceneRadiance)
width = len(sceneRadiance[0])
img_hsv = rgb2hsv(sceneRadiance)
h, s, v = cv2.split(img_hsv)
img_s_stretching = global_stretching(s, height, width)
img_v_stretching = global_stretching(v, height, width)
labArray = np.zeros((height, width, 3), 'float64')
labArray[:, :, 0] = h
labArray[:, :, 1] = img_s_stretching
labArray[:, :, 2] = img_v_stretching
img_rgb = hsv2rgb(labArray) * 255
# img_rgb = np.clip(img_rgb, 0, 255)
return img_rgb
files = natsort.natsorted(files)
for i in range(len(files)):
file = files[i]
filepath = path + "/" + file
prefix = file.split('.')[0]
if os.path.isfile(filepath):
print('******** file ********', file)
img = cv2.imread(folder + '/InputImages/' + file)
blockSize = 9
gimfiltR = 50 # 引导滤波时半径的大小
eps = 10**-3 # 引导滤波时epsilon的值
DepthMap = depthMap(img)
DepthMap = global_stretching(DepthMap)
guided_filter = GuidedFilter(img, gimfiltR, eps)
refineDR = guided_filter.filter(DepthMap)
refineDR = np.clip(refineDR, 0, 1)
cv2.imwrite('ULAPDepthMap.jpg', np.uint8(refineDR * 255))
plt.subplot(311), plt.imshow(np.uint8(refineDR * 255))
plt.show()
AtomsphericLight = BLEstimation(img, DepthMap) * 255
d_0 = minDepth(img, AtomsphericLight)
d_f = 8 * (DepthMap + d_0)
transmissionB, transmissionG, transmissionR = getRGBTransmissionESt(
d_f)
AtomsphericLight = ThreeAtomsphericLightFusion(AtomsphericLightOne,
AtomsphericLightTwo,
AtomsphericLightThree,
img)
print('AtomsphericLight', AtomsphericLight) # [b,g,r]
R_map = max_R(img, blockSize)
mip_map = R_minus_GB(img, blockSize, R_map)
bluriness_map = BlurrnessMap
d_R = 1 - StretchingFusion(R_map)
d_D = 1 - StretchingFusion(mip_map)
d_B = 1 - StretchingFusion(bluriness_map)
d_n = Scene_depth(d_R, d_D, d_B, img, AtomsphericLight)
d_n_stretching = global_stretching(d_n)
d_0 = closePoint(img, AtomsphericLight)
d_f = 8 * (d_n + d_0)
# cv2.imwrite('OutputImages/' + prefix + '_IBLADepthMapd_D.jpg', np.uint8((d_D)*255))
# cv2.imwrite('OutputImages/' + prefix + '_IBLADepthMap.jpg', np.uint8((d_f/d_f.max())*255))
transmissionR = getTransmission(d_f)
transmissionB, transmissionG = getGBTransmissionESt(
transmissionR, AtomsphericLight)
transmissionB, transmissionG, transmissionR = Refinedtransmission(
transmissionB, transmissionG, transmissionR, img)
# cv2.imwrite('OutputImages/' + prefix + '_IBLA_TM.jpg', np.uint8(np.clip(transmissionR * 255, 0, 255)))
sceneRadiance = sceneRadianceRGB(img, transmissionB, transmissionG,
