Low-Illuminance Texture Image Enhancement Method Based on SCBSO Algorithm

Zhiyong Tao; Lei Zhang; Sen Lin

doi:10.3788/LOP56.241002

Journals >Laser & Optoelectronics Progress >Volume 56 >Issue 24 >Page 241002 > Article

Laser & Optoelectronics Progress
Vol. 56, Issue 24, 241002 (2019)

Low-Illuminance Texture Image Enhancement Method Based on SCBSO Algorithm

Zhiyong Tao, Lei Zhang^*, and Sen Lin

Author Affiliations

School of Electronic and Information Engineering, Liaoning Technical University, Fuxin, Liaoning 114000, China

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DOI: 10.3788/LOP56.241002 Cite this Article Set citation alerts

Zhiyong Tao, Lei Zhang, Sen Lin. Low-Illuminance Texture Image Enhancement Method Based on SCBSO Algorithm[J]. Laser & Optoelectronics Progress, 2019, 56(24): 241002 Copy Citation Text

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Fig. 1. Schematic of chromosome structure

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Schematics of chromosome structure before and after mapping. (a) Distribution of gray value of original image; (b) gray value distribution of remapped image; (c) original chromosome structure; (d) remapped chromosome structure

Fig. 2. Schematics of chromosome structure before and after mapping. (a) Distribution of gray value of original image; (b) gray value distribution of remapped image; (c) original chromosome structure; (d) remapped chromosome structure

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Fig. 3. Flowchart of SCBSO algorithm

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Fig. 4. Image enhancement method for simple chromosome structure of SCBSO

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Fig. 5. Iterative curves of four algorithms for f₁(x) function

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Fig. 6. Iterative curves of four algorithms for f₂(x) function

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Fig. 7. Image collected in database

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Fig. 8. Image extracted in ROI

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Fig. 9. Experimental image 1 enhanced by different algorithms. (a) Enhanced image of original image; (b) image enhanced by BSO; (c) image enhanced by GA; (d) image enhanced by SCBSO

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Fig. 10. Gray histograms of images enhanced by different algorithms. (a) Gray histogram of original image; (b) gray histogram enhanced by BSO; (c) gray histogram enhanced by GA; (d) gray histogram enhanced by SCBSO

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Fig. 11. Experimental image 2 enhanced by different algorithms. (a) Original image; (b) image enhanced by BSO; (c) image enhanced by GA; (d) image enhanced by SCBSO

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Fig. 12. Gray histograms of image 2 enhanced by different algorithms. (a) Gray histogram of original image; (b) gray histogram enhanced by BSO; (c) gray histogram enhanced by GA; (d) gray histogram enhanced by SCBSO

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Function	Dimension ofindependent variable	Range ofindependent variables	Function minimum
f₁(x)= $\begin{matrix} \overset{n}{\sum_{i = 1}} \end{matrix} \begin{matrix} \|x_{i}\| \end{matrix}$ + $\begin{matrix} \prod_{i}^{=} \end{matrix} \begin{matrix} \|x_{i}\| \end{matrix}$	30	[-10,10]	0
f₂(x)= $\begin{matrix} \overset{n}{\sum_{i = 1}} \end{matrix}$ -x_isin( $\begin{matrix} \sqrt[]{\|x_{i}\|} \end{matrix}$ )	30	[-50,50]	-418.9829×n

Table 1. Results of benchmark function test

Function	Algorithm	Function mean	Variance	Time /s
	SCBSO	0	0	0.398
f₁(x)= $\begin{matrix} \overset{n}{\sum_{i = 1}} \end{matrix} \begin{matrix} \|x_{i}\| \end{matrix}$ + $\begin{matrix} \prod_{i}^{=} \end{matrix} \begin{matrix} \|x_{i}\| \end{matrix}$	BSO	1.130×10^-4	3.5700×10^-4	0.477
	PSO	1.225	3.2740	0.401
	GA	0.005	0.0032	1.127
	SCBSO	-12569	5.4210	0.421
f₂(x)= $\begin{matrix} \overset{n}{\sum_{i = 1}} \end{matrix}$ -x_isin( $\begin{matrix} \sqrt[]{\|x_{i}\|} \end{matrix}$ )	BSO	-12214	271.4000	0.494
	PSO	-10989	624.7000	0.417
	GA	-9984	2464.2000	1.629

Table 2. Comparison of function performances of different algorithms

Image	Method	LOE	VIF	PSNR
	SCBSO	37.124	1.1074	18.662
Image1	BSO	70.487	0.7219	16.096
	GA	45.815	1.0119	17.486
	SCBSO	30.223	1.2471	20.095
Image2	BSO	39.912	1.0891	18.781
	GA	38.351	1.1299	19.813

Table 3. Objective evaluation index of images enhanced by different algorithms

Image	Method	LOE	VIF	PSNR
	SCBSO	40.925	1.1219	19.742
Database 1	BSO	65.797	0.9733	17.844
	GA	47.584	1.0174	18.978
	SCBSO	31.595	1.2146	20.846
Database 2	BSO	40.362	1.0941	19.461
	GA	39.432	1.1764	18.456

Table 4. Average indexes of different methods on 40 images

Zhiyong Tao, Lei Zhang, Sen Lin. Low-Illuminance Texture Image Enhancement Method Based on SCBSO Algorithm[J]. Laser & Optoelectronics Progress, 2019, 56(24): 241002

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