Multi-scale enhancement and color depth codec correction of flotation foam low illumination images

Method	Comentropy	Contrast	Resolution	Texture correlation/%	PSNR/dB
Low illumination foam image	6.397 0	22.300 8	12.114 0	20.93	24.043 1
Method in Ref.［13］	7.200 7	22.453 3	15.758 5	7.82	14.582 2
Method in Ref.［14］	6.682 7	50.603 8	19.868 1	12.87	15.011 4
Method in Ref.［15］	6.508 4	30.750 9	16.368 4	9.30	24.706 1
Method in Ref.［9］	7.540 5	59.052 4	24.614 3	23.13	25.867 0
Proposed method	7.683 1	61.431 6	25.677 8	24.71	26.391 7

Table 2. Comparison of the performance of the methods on LZFF dataset

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Table 2. Comparison of the performance of the methods on LZFF dataset

Method	PSNR/dB↑	SSIM↑	CIEDE↓
Zero-DCE^［16］	16.841	0.510	24.440
HDRNet^［17］	9.910	0.594	21.338
LCDPNet^［18］	10.995	0.304	21.211
LA-Net^［19］	20.727	0.599	6.728
RUAS^［20］	19.577	0.632	5.497
MSRCR^［10］	10.861	0.278	21.387
ZeroIG^［21］	9.318	0.153	35.890
GDNet^［22］	15.246	0.789	18.686
LYT-Net^［23］	20.813	0.750	11.720
Proposed method	24.090	0.841	1.007

Table 3. Comparison of the performance of the methods on LRFF dataset

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Table 3. Comparison of the performance of the methods on LRFF dataset

Method	PSNR/dB↑	SSIM↑	CIEDE↓
Zero-DCE^［16］	6.876	0.290	83.815
HDRNet^［17］	7.956	0.390	72.202
LCDPNet^［18］	5.859	0.181	91.877
LA-Net^［19］	27.348	0.872	3.734
RUAS^［20］	9.212	0.372	62.047
MSRCR^［10］	9.930	0.451	51.305
ZeroIG^［21］	8.660	0.365	68.310
GDNet^［22］	21.729	0.830	5.965
LYT-Net^［23］	24.922	0.835	5.283
Proposed method	28.461	0.905	2.502

Table 4. Comparison of the performance of the methods on the Low-Light dataset

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Table 4. Comparison of the performance of the methods on the Low-Light dataset

Method	PSNR/dB↑	SSIM↑	CIEDE↓
Zero-DCE^［16］	9.406	0.353	43.697
HDRNet^［17］	14.734	0.622	45.445
LCDPNet^［18］	10.239	0.357	53.697
LA-Net^［19］	23.387	0.869	15.375
RUAS^［20］	13.067	0.680	14.826
MSRCR^［10］	14.210	0.523	18.681
ZeroIG^［21］	18.835	0.712	13.147
GDNet^［22］	23.746	0.784	17.131
LYT-Net^［22］	16.545	0.799	14.804
Proposed method	21.657	0.872	10.088

Table 5. Denoising and edge detection performance statistics of each method on Low-Light dataset

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Table 5. Denoising and edge detection performance statistics of each method on Low-Light dataset

Noise variance	Index	RUAS	LA-Net	HDRNet	Method in Ref.［20］	Method in Ref.［14］	Method in Ref.［9］	Proposed method
10%	PSNR/dB	14.191 1	22.608 8	12.455 2	22.812 7	22.903 9	23.271 3	23.874 8
10%	EPI/%	0.551 9	0.662 7	0.569 3	0.332 3	0.189 5	0.647 2	0.690 9
20%	PSNR/dB	14.186 0	22.520 1	12.291 7	22.780 2	21.903 3	22.294 3	22.684 1
20%	EPI/%	0.547 8	0.664 6	0.568 1	0.337 4	0.194 1	0.635 8	0.675 7
30%	PSNR/dB	14.130 0	22.333 5	11.275 1	21.782 6	20.909 4	21.392 6	21.524 2
30%	EPI/%	0.543 0	0.660 8	0.556 1	0.520 2	0.588 1	0.661 8	0.663 5

Table 6. Denoising and edge detection performance statistics of each method on LZFF dataset

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Table 6. Denoising and edge detection performance statistics of each method on LZFF dataset

Noise variance	Index	RUAS	LA-Net	HDRNet	Method in Ref.［20］	Method in Ref.［14］	Method in Ref.［9］	Proposed method
10%	PSNR/dB	14.191 1	22.608 8	12.455 2	22.812 7	22.903 9	23.271 3	23.874 8
10%	EPI/%	0.551 9	0.662 7	0.569 3	0.332 3	0.189 5	0.647 2	0.690 9
20%	PSNR/dB	14.186 0	22.520 1	12.291 7	22.780 2	21.903 3	22.294 3	22.684 1
20%	EPI/%	0.547 8	0.664 6	0.568 1	0.337 4	0.194 1	0.635 8	0.675 7
30%	PSNR/dB	14.130 0	22.333 5	11.275 1	21.782 6	20.909 4	21.392 6	21.524 2
30%	EPI/%	0.543 0	0.660 8	0.556 1	0.520 2	0.588 1	0.661 8	0.663 5

Table 7. Ablation study of CDCC-Net modules on LZFF dataset
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Table 7. Ablation study of CDCC-Net modules on LZFF dataset
Backbone GSM SimA PSNR/dB↑ SSIM↑ CIEDE↓
√ 22.438 0.815 3.572
√ √ 23.696 0.835 3.719
√ √ 22.604 0.825 3.644
√ √ √ 24.090 0.841 2.313

Table 8. Ablation study of color space on LZFF dataset

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Table 8. Ablation study of color space on LZFF dataset

Color Space	CDCC-Net	Proseed method of V	PSNR/dB↑	SSIM↑
LAB	√		22.209	0.717
		√	21.552	0.805
	√	√	22.397	0.829
LCH	√		21.274	0.824
		√	21.519	0.784
	√	√	22.681	0.837
HIS	√		23.853	0.826
		√	23.044	0.845
	√	√	24.916	0.893
HSV	√		24.090	0.841
		√	23.281	0.857
	√	√	29.062	0.930

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Lei SUN, Qian TANG, Yipeng LIAO, Yuhua LIAO, Zexi DONG, Jianjun HE. Multi-scale enhancement and color depth codec correction of flotation foam low illumination images[J]. Optics and Precision Engineering, 2025, 33(10): 1609

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Paper Information

Category:

Received: Dec. 17, 2024

Accepted: --

Published Online: Jul. 23, 2025

The Author Email: Yipeng LIAO (fzu_lyp@163.com)

DOI:10.37188/OPE.20253310.1609

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology

Table 1. Comparison of the enhancement of each method on three different working condition foam datasets

Table 1. Comparison of the enhancement of each method on three different working condition foam datasets

Table 2. Comparison of the performance of the methods on LZFF dataset

Table 2. Comparison of the performance of the methods on LZFF dataset

Table 3. Comparison of the performance of the methods on LRFF dataset

Table 3. Comparison of the performance of the methods on LRFF dataset

Table 4. Comparison of the performance of the methods on the Low-Light dataset

Table 4. Comparison of the performance of the methods on the Low-Light dataset

Table 5. Denoising and edge detection performance statistics of each method on Low-Light dataset

Table 5. Denoising and edge detection performance statistics of each method on Low-Light dataset

Table 6. Denoising and edge detection performance statistics of each method on LZFF dataset

Table 6. Denoising and edge detection performance statistics of each method on LZFF dataset

Table 7. Ablation study of CDCC-Net modules on LZFF dataset

Table 7. Ablation study of CDCC-Net modules on LZFF dataset

Table 8. Ablation study of color space on LZFF dataset

Table 8. Ablation study of color space on LZFF dataset