Low-Illumination Image Enhancement Algorithm Based on Parallel Residual Network

Table 1. Calculation results of PSNR and SSIM for different combinations of loss functions
View table
Table 1. Calculation results of PSNR and SSIM for different combinations of loss functions
Loss PSNR SSIM
L'₁ 23.039 0.7947
L'₂ 24.833 0.8269
L'₃ 27.149 0.8434
L'₄ 27.375 0.8807

Table 2. PSNR and SSIM of our algorithm and seven contrast algorithms on real dataset

View table

Table 2. PSNR and SSIM of our algorithm and seven contrast algorithms on real dataset

Image	Evaluation index	Method
Image	Evaluation index	SSR	MSRCR	Ying	Ren	BIMEF	LIME	Li	Our
Image1	PSNR /dB	12.059	17.844	14.412	11.884	18.412	21.345	20.447	28.331
Image1	SSIM	0.6013	0.5794	0.5969	0.6835	0.6469	0.7898	0.7259	0.8997
Image2	PSNR/dB	13.469	14.007	20.891	14.558	14.829	23.968	22.424	31.087
Image2	SSIM	0.5974	0.5743	0.7559	0.8232	0.6001	0.8559	0.7068	0.9365
Image3	PSNR/dB	18.612	21.041	15.982	10.920	11.706	17.700	21.346	30.112
Image3	SSIM	0.7810	0.7346	0.8321	0.6560	0.6826	0.7209	0.7881	0.9331
Image4	PSNR/dB	15.931	13.706	20.5662	14.780	15.394	24.355	17.858	25.914
Image4	SSIM	0.6581	0.4831	0.6405	0.6504	0.5674	0.8334	0.6849	0.8343

Table 3. PSNR and SSIM of our algorithm and seven contrast algorithms on synthetic dataset

View table

Table 3. PSNR and SSIM of our algorithm and seven contrast algorithms on synthetic dataset

Image	Evaluation index	Method
Image	Evaluation index	SSR	MSRCR	Ying	Li	Ren	BIMEF	LIME	Our
Image1	PSNR /dB	11.841	13.085	19.501	17.415	13.601	13.863	26.417	29.053
Image1	SSIM	0.6656	0.6802	0.7273	0.7778	0.5221	0.7088	0.8363	0.8416
Image2	PSNR /dB	11.253	11.674	22.293	19.002	15.951	16.218	23.830	29.959
Image2	SSIM	0.6031	0.6240	0.7887	0.8049	0.6541	0.7653	0.8323	0.8746
Image3	PSNR /dB	9.8805	10.946	21.450	16.578	17.093	20.704	20.307	26.423
Image3	SSIM	0.5483	0.5690	0.6863	0.6675	0.4814	0.7687	0.7725	0.8073
Image4	PSNR /dB	12.746	13.868	15.871	15.769	11.287	11.613	20.699	26.085
Image4	SSIM	0.5681	0.6006	0.6715	0.7619	0.4996	0.6513	0.8129	0.8318

Table 4. Information entropy, NRSS and NIQE of low-illumination images without contrast map

View table

Table 4. Information entropy, NRSS and NIQE of low-illumination images without contrast map

Method	Evaluation index							NIQE
Method	Image1	Image2	Image3	Average	Image1	Image2	Image3	Average	Image1	Image2	Image3	Average
SSR	6.3635	7.0093	7.0177	6.7968	0.4208	0.6408	0.4511	0.5042	21.543	30.237	28.735	26.838
MSRCR	6.2553	7.1503	7.1858	6.8305	0.4168	0.6437	0.4847	0.4125	21.173	23.282	13.111	19.189
Ying	4.9771	6.4808	6.8622	6.8638	0.2963	0.5007	0.4406	0.5151	9.352	11.769	9.21	10.11
Li	4.7706	5.6065	6.5899	5.6557	0.3614	0.4961	0.3948	0.4174	11.513	12.074	9.927	11.171
Ren	4.2115	5.6318	6.1182	5.3205	0.3559	0.3442	0.2184	0.3062	9.927	17.351	11.738	13.005
BIMEF	5.3003	6.4905	6.8105	6.2004	0.3445	0.6266	0.5277	0.4996	8.793	17.855	13.26	13.303
LIME	5.9361	6.274	7.153	6.4544	0.4394	0.6492	0.3226	0.4704	8.347	20.275	12.72	13.781
Our	6.5744	6.8264	7.0261	6.809	0.3772	0.6425	0.6024	0.5407	8.269	11.727	7.593	9.196

Table 5. PSNR and SSIM results of four network models
View table
Table 5. PSNR and SSIM results of four network models
Model PSNR /dB SSIM
Model1 29.552 0.9026
Model2 29.564 0.9048
Model3 27.942 0.8208
Model4 26.147 0.8321

Table 6. Comparison of running time of four models for enhancement of single image
View table
Table 6. Comparison of running time of four models for enhancement of single image
Image Model
Model1 Model2 Model3 Model4
Synthetic image 0.6572 0.8374 0.5982 0.6067
Real image 0.6497 0.8679 0.5889 0.6164

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Qingjiang Chen, Jinyang Li, Qiannan Hu. Low-Illumination Image Enhancement Algorithm Based on Parallel Residual Network[J]. Laser & Optoelectronics Progress, 2021, 58(14): 1410015

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Paper Information

Category: Image Processing

Received: Oct. 14, 2020

Accepted: Nov. 14, 2020

Published Online: Jun. 30, 2021

The Author Email: Jinyang Li (1057042448@qq.com)

DOI:10.3788/LOP202158.1410015

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology

Table 1. Calculation results of PSNR and SSIM for different combinations of loss functions

Table 1. Calculation results of PSNR and SSIM for different combinations of loss functions

Table 2. PSNR and SSIM of our algorithm and seven contrast algorithms on real dataset

Table 2. PSNR and SSIM of our algorithm and seven contrast algorithms on real dataset

Table 3. PSNR and SSIM of our algorithm and seven contrast algorithms on synthetic dataset

Table 3. PSNR and SSIM of our algorithm and seven contrast algorithms on synthetic dataset

Table 4. Information entropy, NRSS and NIQE of low-illumination images without contrast map

Table 4. Information entropy, NRSS and NIQE of low-illumination images without contrast map

Table 5. PSNR and SSIM results of four network models

Table 5. PSNR and SSIM results of four network models

Table 6. Comparison of running time of four models for enhancement of single image

Table 6. Comparison of running time of four models for enhancement of single image