| TANG Huapeng(唐华鹏),QIN Danyang,YAN Mengying,YANG Jiaqiang,ZHANG Gengxin.[J].高技术通讯(英文),2023,29(1):78~86 |
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| Research on color image matching method based on feature point compensation in dark light environment |
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| DOI：10. 3772/ j. issn. 1006-6748. 2023. 01. 009 |
| 中文关键词: |
| 英文关键词: dark light environment, unsharp masking(USM), denoising model, feature point compensation, fast library for approximate nearest neighbor(FLANN), random sample consensus(RANSAC) |
| 基金项目: |
| Author Name | Affiliation | | TANG Huapeng(唐华鹏) | (School of Electronic Engineering, Heilongjiang University, Harbin 150080, P.R.China) | | QIN Danyang | (School of Electronic Engineering, Heilongjiang University, Harbin 150080, P.R.China) | | YAN Mengying | (School of Electronic Engineering, Heilongjiang University, Harbin 150080, P.R.China) | | YANG Jiaqiang | (School of Electronic Engineering, Heilongjiang University, Harbin 150080, P.R.China) | | ZHANG Gengxin | (School of Electronic Engineering, Heilongjiang University, Harbin 150080, P.R.China) |
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| 中文摘要: |
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| 英文摘要: |
| Image matching refers to the process of matching two or more images obtained at different time, different sensors or different conditions through a large number of feature points in the image. At present, image matching is widely used in target recognition and tracking, indoor positioning and navigation. Local features missing, however, often occurs in color images taken in dark light, making the extracted feature points greatly reduced in number, so as to affect image matching and even fail the target recognition. An unsharp masking (USM) based denoising model is established and a local adaptive enhancement algorithm is proposed to achieve feature point compensation by strengthening local features of the dark image in order to increase amount of image information effectively. Fast library for approximate nearest neighbors (FLANN) and random sample consensus (RANSAC) are image matching algorithms. Experimental results show that the number of effective feature points obtained by the proposed algorithm from images in dark light environment is increased, and the accuracy of image matching can be improved obviously. |
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