Color Constancy Algorithm of Microscopic Images Based on Autoencoder

Fangming Lan; Zongju Peng; Zhihua Lu; Qichao Shi; Fen Chen

doi:10.3788/LOP202158.2010010

Journals >Laser & Optoelectronics Progress >Volume 58 >Issue 20 >Page 2010010 > Article

Laser & Optoelectronics Progress
Vol. 58, Issue 20, 2010010 (2021)

Color Constancy Algorithm of Microscopic Images Based on Autoencoder

Fangming Lan¹, Zongju Peng^1、2、*, Zhihua Lu¹, Qichao Shi¹, and Fen Chen²

Author Affiliations

¹Faculty of Information Science and Engineering, Ningbo University, Ningbo, Zhejiang 315201, China

²School of Electrical and Electronic Engineering, Chongqing University of Technology, Chongqing 400054, China

show less

DOI: 10.3788/LOP202158.2010010 Cite this Article Set citation alerts

Fangming Lan, Zongju Peng, Zhihua Lu, Qichao Shi, Fen Chen. Color Constancy Algorithm of Microscopic Images Based on Autoencoder[J]. Laser & Optoelectronics Progress, 2021, 58(20): 2010010 Copy Citation Text

show less

Fig. 1. Physical image of the microscope and camera. (a) Color temperature is 4500 K; (b) color temperature is 6300 K; (c) color temperature is 7000 K

Download full size

Fig. 2. Statistics of the color cast coefficient. (a) Color temperature is 4500 K; (b) color temperature is 6300 K; (c) color temperature is 7000 K

Download full size

Fig. 3. RAW image generated by simulation. (a) GT; (b) CCM; (c) WB; (d) RAW

Download full size

Fig. 4. Color restoration results of different autoencoders. (a) Original image; (b) autoencoder; (c) UNet autoencoder

Download full size

Fig. 5. Structure of the Inception

Download full size

Fig. 6. Structure of the UNet autoencoder

Download full size

Fig. 7. Subjective results of different algorithms in microscope color constancy dataset. (a) RAW; (b) Ref.[8]; (c) Ref. [9]; (d) Ref. [10] ; (e) Ref. [11]; (f) Ref. [12]; (g) Ref. [13]; (h) Ref. [15] ; (i) ours; (j) GT

Download full size

T	Best25%	Mean	Medium	Trimean	Worst25%
10	1.78	2.40	2.01	2.12	7.05
20	1.75	2.36	2.00	2.09	6.56
30	1.62	2.32	2.36	2.01	6.34
40	1.55	2.30	2.09	1.97	5.98
50	1.43	2.29	1.91	1.93	5.52
60	1.29	2.25	1.79	1.90	5.13
70	1.11	2.23	1.76	1.85	4.98
80	1.02	2.12	1.70	1.80	4.78
90	0.92	2.01	1.67	1.72	4.05
100	1.04	2.08	1.69	1.75	4.28
110	1.23	2.18	1.72	1.79	4.78
120	1.11	2.21	1.75	1.82	5.06
130	1.33	2.22	1.89	1.92	5.98
140	1.42	2.26	1.94	1.98	6.25
150	1.48	2.35	1.98	2.01	6.43
160	1.53	2.39	2.02	2.06	6.52
170	1.62	2.35	2.05	2.09	6.75
180	1.72	2.45	2.08	2.14	7.12

Table 1. Selection of threshold T

Algorithm	Best25%	Mean	Medium	Trimean	Worst25%
GW^[8]	1.16	4.59	3.46	3.81	9.85
WP^[9]	1.44	9.91	7.44	8.78	21.27
Quasi-unsupervised^[14]	--	1.97	1.91	--	--
CM^[16]	0.50	2.25	1.59	1.74	5.13
Ref.[15]	0.52	2.05	1.50	--	4.48
Ref.[12]	0.46	2.18	1.48	1.64	5.03
Ref.[17]	0.50	2.39	1.61	1.74	5.67
Ref.[17]( pretrained)	0.46	2.35	1.55	1.73	5.62
CNN^[13]	0.68	2.14	1.83	1.95	4.26
UNet^[19]	1.13	2.56	2.04	2.23	5.17
Ours	0.92	2.01	1.67	1.72	4.05

Table 2. Evaluation results of different algorithms in NUS-8 CC dataset

Algorithm	Best25%	Mean	Medium	Trimean	Worst25%
GW^[8]	5.00	9.70	10.00	10.00	13.70
WP^[9]	2.20	9.10	6.70	7.80	18.90
SoG^[10]	2.30	7.30	6.80	6.90	12.80
GE^[11]	0.70	5.50	3.30	3.90	13.80
CC-GANs (Pix2Pix)^[18]	1.20	3.60	2.80	3.10	7.20
CC-GANs(CycleGAN)^[18]	0.70	3.40	2.60	2.80	7.30
CC-GANs (StarGAN)^[18]	1.70	5.70	4.90	5.20	10.50
CNN^[13]	0.80	2.60	2.00	2.10	4.00
UNet^[19]	1.17	2.98	2.45	2.71	5.29
Ours	0.96	2.35	2.05	2.18	3.98

Table 3. Evaluation results of different algorithms in RECommended CC dataset

Algorithm	Best25%	Mean	Medium	Trimean	Worst25%
GW^[8]	2.26	5.77	4.81	5.07	11.94
WP^[9]	4.43	6.19	5.04	5.21	10.60
SoG^[10]	1.01	3.59	3.17	3.18	7.51
GE^[11]	4.29	6.73	6.24	6.39	11.42
Ref.[12]	1.43	3.70	3.17	3.26	7.55
Ref.[15]	3.57	5.70	5.54	5.53	9.76
CNN^[13]	0.75	1.98	1.75	1.81	4.25
UNet^[19]	0.67	1.56	1.34	1.45	3.16
Ours	0.43	0.97	0.75	0.79	2.08

Table 4. Evaluation results of different algorithms in self-built microscope CC dataset

Fangming Lan, Zongju Peng, Zhihua Lu, Qichao Shi, Fen Chen. Color Constancy Algorithm of Microscopic Images Based on Autoencoder[J]. Laser & Optoelectronics Progress, 2021, 58(20): 2010010

Download Citation

Set citation alerts for the article

Tools

Set citation alerts for the article

Save the article for my favorites

Paper Information