BM-IQE: An image quality evaluator with block-matching for both real-life scenes and remote sensing scenes
文献类型：期刊论文
| 作者 | Huang, Yongmei2; Ren, Guoqiang2; Ma, Dongao3; Xu, Ningshan1,2 |
| 刊名 | Sensors
 |
| 出版日期 | 2020-06-01 |
| 卷号 | 20期号:12页码:1-24 |
| 关键词 | imaging performance blind image quality assessment block-matching remote sensing |
| ISSN号 | 1424-8220 |
| DOI | 10.3390/s20123472 |
| 文献子类 | 期刊论文 |
| 英文摘要 | Like natural images, remote sensing scene images; of which the quality represents the imaging performance of the remote sensor, also suffer from the degradation caused by imaging system. However, current methods measuring the imaging performance in engineering applications require for particular image patterns and lack generality. Therefore, a more universal approach is demanded to assess the imaging performance of remote sensor without constraints of land cover. Due to the fact that existing general-purpose blind image quality assessment (BIQA) methods cannot obtain satisfying results on remote sensing scene images; in this work, we propose a BIQA model of improved performance for natural images as well as remote sensing scene images namely BM-IQE. We employ a novel block-matching strategy called Structural Similarity Block-Matching (SSIM-BM) to match and group similar image patches. In this way, the potential local information among different patches can get expressed; thus, the validity of natural scene statistics (NSS) feature modeling is enhanced. At the same time, we introduce several features to better characterize and express remote sensing images. The NSS features are extracted from each group and the feature vectors are then fitted to a multivariate Gaussian (MVG) model. This MVG model is therefore used against a reference MVG model learned from a corpus of high-quality natural images to produce a basic quality estimation of each patch (centroid of each group). The further quality estimation of each patch is obtained by weighting averaging of its similar patches’ basic quality estimations. The overall quality score of the test image is then computed through average pooling of the patch estimations. Extensive experiments demonstrate that the proposed BM-IQE method can not only outperforms other BIQA methods on remote sensing scene image datasets but also achieve competitive performance on general-purpose natural image datasets as compared to existing state-of-the-art FR/NR-IQA methods. © 2020 by the authors. Licensee MDPI, Basel, Switzerland. |
| 出版地 | BASEL |
| WOS关键词 | STATISTICS |
| WOS研究方向 | Chemistry ; Engineering ; Instruments & Instrumentation |
| 语种 | 英语 |
| WOS记录号 | WOS:000553139900001 |
| 出版者 | MDPI |
| 源URL | [http://ir.ioe.ac.cn/handle/181551/10142]  |
| 专题 | 薄膜光学相机总体室 |
| 作者单位 | 1.The School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing; 100049, China; 2.Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu; 610209, China; 3.Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing; 100101, China |
| 推荐引用方式 GB/T 7714 | Huang, Yongmei,Ren, Guoqiang,Ma, Dongao,et al. BM-IQE: An image quality evaluator with block-matching for both real-life scenes and remote sensing scenes[J]. Sensors,2020,20(12):1-24. |
| APA | Huang, Yongmei,Ren, Guoqiang,Ma, Dongao,&Xu, Ningshan.(2020).BM-IQE: An image quality evaluator with block-matching for both real-life scenes and remote sensing scenes.Sensors,20(12),1-24. |
| MLA | Huang, Yongmei,et al."BM-IQE: An image quality evaluator with block-matching for both real-life scenes and remote sensing scenes".Sensors 20.12(2020):1-24. |
入库方式： OAI收割
来源：光电技术研究所
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