Image fusion based on multiscale transform and sparse representation to enhance terahertz images
文献类型：期刊论文
| 作者 | Mao, Qi2; Zhu, Yunlong4; Lv, Cixing1; Lu, Yao1; Yan, Xiaohui1; Wei, Dongshan1; Yan, Shihan3 ; Liu, Jingbo1
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| 刊名 | OPTICS EXPRESS
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| 出版日期 | 2020-08-17 |
| 卷号 | 28期号:17页码:25293-25307 |
| ISSN号 | 1094-4087 |
| DOI | 10.1364/OE.396604 |
| 通讯作者 | Zhu, Yunlong(zyl@fudan.edu.cn) ; Lv, Cixing(cixinglv@163.com) |
| 英文摘要 | High-quality terahertz (THz) images are vital to integrated circuit (IC) manufacturing. Due to the unique sensitivity of THz waves to different materials, the images obtained from the point-spread function (PSF) model have fewer image details and less texture information in some frequency bands. This paper presents an image fusion technique to enhance the resolution of THz IC images. The source images obtained from the PSF model are processed by a fusion method combining a multiscale transform (MST) and sparse representation (SR). The low-pass band is handled by sparse representation, and the high-pass band is fused by the conventional "max-absolute" rule. From both objective and visual perspectives, four popular multiscale transforms-the Laplacian pyramid, the ratio of low-pass pyramids, the dual-tree complex wavelet transform and the curvelet transform-are thoroughly compared at different decomposition levels ranging from one to four. This work demonstrates the feasibility of using image fusion to enhance the resolution of THz IC images. (C) 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement |
| 资助项目 | National Key Research and Development Program of China[2018YFB1004004] ; National Key Research and Development Program of China[2018YFB1702701] |
| WOS研究方向 | Optics |
| 语种 | 英语 |
| WOS记录号 | WOS:000560936200078 |
| 出版者 | OPTICAL SOC AMER |
| 源URL | [http://119.78.100.138/handle/2HOD01W0/11705]  |
| 专题 | 中国科学院重庆绿色智能技术研究院 |
| 通讯作者 | Zhu, Yunlong; Lv, Cixing |
| 作者单位 | 1.Dongguan Univ Technol, Sch Elect Engn & Intelligentizat, Dongguan 523808, Peoples R China 2.Dongbei Univ Finance & Econ, Sch Management Sci & Engn, Dalian 116025, Peoples R China 3.Chongqing Inst Green & Intelligent Technol, Chongqing Engn Res Ctr High Resolut & Three Dimen, Chongqing 400714, Peoples R China 4.Fudan Univ, Acad Engn & Technol, Shanghai 200433, Peoples R China |
| 推荐引用方式 GB/T 7714 | Mao, Qi,Zhu, Yunlong,Lv, Cixing,et al. Image fusion based on multiscale transform and sparse representation to enhance terahertz images[J]. OPTICS EXPRESS,2020,28(17):25293-25307. |
| APA | Mao, Qi.,Zhu, Yunlong.,Lv, Cixing.,Lu, Yao.,Yan, Xiaohui.,...&Liu, Jingbo.(2020).Image fusion based on multiscale transform and sparse representation to enhance terahertz images.OPTICS EXPRESS,28(17),25293-25307. |
| MLA | Mao, Qi,et al."Image fusion based on multiscale transform and sparse representation to enhance terahertz images".OPTICS EXPRESS 28.17(2020):25293-25307. |
入库方式： OAI收割
来源：重庆绿色智能技术研究院
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