Rrg-gan restoring network for simple lens imaging system

doi:10.3390/s21103317

CIOMP OpenIR

	Rrg-gan restoring network for simple lens imaging system
	X. Wu; J. Li; G. Zhou; B. Lu; Q. Li and H. Yang
	2021
发表期刊	Sensors
ISSN	14248220
卷号	21 期号:10
摘要	The simple lens computational imaging method provides an alternative way to achieve high-quality photography. It simplifies the design of the optical-front-end to a single-convex-lens and delivers the correction of optical aberration to a dedicated computational restoring algorithm. Traditional single-convex-lens image restoration is based on optimization theory, which has some shortcomings in efficiency and efficacy. In this paper, we propose a novel Recursive Residual Groups network under Generative Adversarial Network framework (RRG-GAN) to generate a clear image from the aberrations-degraded blurry image. The RRG-GAN network includes dual attention module, selective kernel network module, and residual resizing module to make it more suitable for the non-uniform deblurring task. To validate the evaluation algorithm, we collect sharp/aberration-degraded datasets by CODE V simulation. To test the practical application performance, we built a display-capture lab setup and reconstruct a manual registering dataset. Relevant experimental comparisons and actual tests verify the effectiveness of our proposed method. 2021 by the authors. Licensee MDPI, Basel, Switzerland.
DOI	10.3390/s21103317
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收录类别	SCI ; EI
引用统计
文献类型	期刊论文
条目标识符	http://ir.ciomp.ac.cn/handle/181722/65607
专题	中国科学院长春光学精密机械与物理研究所
推荐引用方式 GB/T 7714	X. Wu,J. Li,G. Zhou,et al. Rrg-gan restoring network for simple lens imaging system[J]. Sensors,2021,21(10).
APA	X. Wu,J. Li,G. Zhou,B. Lu,&Q. Li and H. Yang.(2021).Rrg-gan restoring network for simple lens imaging system.Sensors,21(10).
MLA	X. Wu,et al."Rrg-gan restoring network for simple lens imaging system".Sensors 21.10(2021).

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