Salient Detection of Multisource Image Illumination and Edge Fusion

Yuhao Ning; Yu Liu; Shaochu Wang

doi:10.3788/LOP202158.1615005

Journals >Laser & Optoelectronics Progress >Volume 58 >Issue 16 >Page 1615005 > Article

Laser & Optoelectronics Progress
Vol. 58, Issue 16, 1615005 (2021)

Salient Detection of Multisource Image Illumination and Edge Fusion

Yuhao Ning¹, Yu Liu¹, and Shaochu Wang^1、2、*

Author Affiliations

¹School of Microelectronics, Tianjin University, Tianjin 300072, China

²Tianjin Institute of Surveying and Mapping Co., Ltd., Tianjin 300381, China

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DOI: 10.3788/LOP202158.1615005 Cite this Article Set citation alerts

Yuhao Ning, Yu Liu, Shaochu Wang. Salient Detection of Multisource Image Illumination and Edge Fusion[J]. Laser & Optoelectronics Progress, 2021, 58(16): 1615005 Copy Citation Text

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Fig. 1. Architecture of proposed algorithm

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Fig. 2. Block diagram of RGB-T image detail information fusion

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Fig. 3. Architecture of the proposed FSDNet module

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Fig. 4. Salient map comparison between different algorithms. (a) RGB images; (b) T images; (c) EGNet; (d) EGNet+;(e) CPDNet; (f) CPDNet+; (g) PoolNet; (h) PoolNet+; (i) DMRA; (j) A2dele; (k) proposed algorithm; (l) GT

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Fig. 5. P-R curves of different algorithms at different datasets. (a) VT821; (b) VT1000

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Fig. 6. Qualitative comparison of salient maps for ablation analysis. (a) RGB images; (b) T images; (c) Baseline; (d) +I; (e) +IA; (f) proposed algorithm; (g) -E; (h) GT

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Condition	L1	L2	L3	L4	L5	L6	L7	L8	L9
U	0.15	0.25	0.35	0.45	0.55	0.65	0.75	0.85	1
Q	0	0.15	0.25	0.35	0.45	0.55	0.65	0.75	0.85

Table 1. RGB, T image illumination classification

Parameter	L1	L2	L3	L4	L5	L6	L7	L8	L9
η	0.9	0.8	0.7	0.6	0.5	0.4	0.3	0.2	0.1

Table 2. RGB, T image light fusion ratio

Parameter	R1	R2	R3	R4	R5	R6
σ	2	3	4	5	6	7
K	2	4	5	7	8	10

Table 3. Detail information extraction of RGB、T image

L	L1	L2	L3	L4	L5	L6	L7	L8	L9
D	R6	R6	R5	R4	R3	R2	R2	R1	R1

Table 4. RGB、T Image fusion rules

Algorithm	VT821			VT1000
Algorithm	F_max	F_ave	MAE	F_max	F_ave	MAE
EGNet	0.7717	0.7459	0.0512	0.8796	0.8637	0.0400
EGNet+	0.6994	0.6475	0.116	0.7840	0.7453	0.0938
CPDNet	0.7971	0.7882	0.0425	0.8869	0.8621	0.0326
CPDNet+	0.7915	0.7796	0.0471	0.8738	0.8570	0.0333
PoolNet	0.8192	0.8046	0.0485	0.8795	0.8651	0.0411
PoolNet+	0.8177	0.8086	0.0411	0.8759	0.8656	0.0313
DMRA	0.8411	0.8270	0.0417	0.8613	0.8444	0.0381
A2dele	0.7513	0.7482	0.0621	0.8609	0.8575	0.0401
CGL	0.780	0.744	0.0849		0.727
CRA	0.747	0.739	0.1083		0.693
Proposed algorithm	0.8433	0.8291	0.0375	0.9095	0.8943	0.0268

Table 5. Quantitative comparison of different algorithms

Algorithm	F_max	F_ave	MAE
EGNet	0.6602	0.5825	0.1100
EGNet+	0.8393	0.8136	0.0616
EGNet++	0.8225	0.8036	0.0538
CPDNet	0.7662	0.7092	0.1060
CPDNet+	0.8071	0.7827	0.0721
CPDNet++	0.8164	0.8038	0.0546
PoolNet	0.5803	0.5578	0.1140
PoolNet+	0.7922	0.7683	0.0622
PoolNet++	0.7532	0.7135	0.0940
Proposed algorithm	0.8743	0.8651	0.0386

Table 6. Test results in VT1000 low light data subset

Algorithm	VT821			VT1000
Algorithm	F_max	F_ave	MAE	F_max	F_ave	MAE
Baseline	0.8256	0.8003	0.0445	0.8396	0.8315	0.0361
+I	0.8326	0.8125	0.0429	0.8459	0.8361	0.0342
+IA	0.8493	0.8139	0.0417	0.8956	0.8827	0.0330
Proposed algorithm	0.8433	0.8291	0.0375	0.9095	0.8943	0.0268
-E	0.8366	0.8193	0.0411	0.9051	0.8819	0.0271

Table 7. Quantitative comparison results of ablation analysis

Yuhao Ning, Yu Liu, Shaochu Wang. Salient Detection of Multisource Image Illumination and Edge Fusion[J]. Laser & Optoelectronics Progress, 2021, 58(16): 1615005

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