Solder joint image adaptive block compressive sensing with convex optimisation and Gini index
This study aims to improve the performance in solder joint image compression and reconstruction. A novel adaptive block compressive sensing with convex optimisation and Gini index (Ad_BCSGB_Gini) methodology for solder joint image compression and reconstruction is proposed. At first, the image is sp...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2019-10-01
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| Series: | The Journal of Engineering |
| Subjects: | |
| Online Access: | https://digital-library.theiet.org/content/journals/10.1049/joe.2018.9148 |
| _version_ | 1818960406259957760 |
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| author | Huihuang Zhao Yaonan Wang Jinhua Zheng Zhijun Qiao Yun Zhang |
| author_facet | Huihuang Zhao Yaonan Wang Jinhua Zheng Zhijun Qiao Yun Zhang |
| author_sort | Huihuang Zhao |
| collection | DOAJ |
| description | This study aims to improve the performance in solder joint image compression and reconstruction. A novel adaptive block compressive sensing with convex optimisation and Gini index (Ad_BCSGB_Gini) methodology for solder joint image compression and reconstruction is proposed. At first, the image is split into square blocks and each block is resized into a row which consists of a new image. Then, the new image is transformed into a sparse signal by an orthogonal basis matrix, and the image reconstruction is handled as a convex optimisation problem. Moreover, a gradient-based method which has fast computational speed is used to reconstruct image. There is a control factor which controls a norm l(1) in the optimisation problem. To achieve the best performance, at last, the proposed method adaptively selects the best result by comparing Gini index of the reconstruction results based on different control factor values. Experimental results with different methods indicate that the Ad_BCSGB_Gini method is able to achieve the best performance in quantisation comparison than several classical algorithms, and Ad_BCSGB_Gini has a good robustness. |
| first_indexed | 2024-12-20T11:57:01Z |
| format | Article |
| id | doaj.art-19e85b372c5047e98a2cb1719b563f1f |
| institution | Directory Open Access Journal |
| issn | 2051-3305 |
| language | English |
| last_indexed | 2024-12-20T11:57:01Z |
| publishDate | 2019-10-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Journal of Engineering |
| spelling | doaj.art-19e85b372c5047e98a2cb1719b563f1f2022-12-21T19:41:37ZengWileyThe Journal of Engineering2051-33052019-10-0110.1049/joe.2018.9148JOE.2018.9148Solder joint image adaptive block compressive sensing with convex optimisation and Gini indexHuihuang Zhao0Yaonan Wang1Jinhua Zheng2Zhijun Qiao3Yun Zhang4College of Computer Science and Technology, Hengyang Normal UniversityCollege of Electrical and Information Engineering, Hunan UniversityCollege of Computer Science and Technology, Hengyang Normal UniversityUniversity of Texas, Rio Grande ValleyInstitute of Radio and TV Technology, Communication University of ZhejiangThis study aims to improve the performance in solder joint image compression and reconstruction. A novel adaptive block compressive sensing with convex optimisation and Gini index (Ad_BCSGB_Gini) methodology for solder joint image compression and reconstruction is proposed. At first, the image is split into square blocks and each block is resized into a row which consists of a new image. Then, the new image is transformed into a sparse signal by an orthogonal basis matrix, and the image reconstruction is handled as a convex optimisation problem. Moreover, a gradient-based method which has fast computational speed is used to reconstruct image. There is a control factor which controls a norm l(1) in the optimisation problem. To achieve the best performance, at last, the proposed method adaptively selects the best result by comparing Gini index of the reconstruction results based on different control factor values. Experimental results with different methods indicate that the Ad_BCSGB_Gini method is able to achieve the best performance in quantisation comparison than several classical algorithms, and Ad_BCSGB_Gini has a good robustness.https://digital-library.theiet.org/content/journals/10.1049/joe.2018.9148matrix algebraiterative methodsdata compressionoptimisationgradient methodssurface mount technologyimage reconstructioncompressed sensingsoldersimage codingmechanical engineering computingad_bcsgb_gini methodsolder joint image reconstruction performancecomparing gini indexconvex optimisation problemsquare blocksnovel adaptive block compressive sensingsolder joint image compressionsurface mount technology componentssolder joint image adaptive block compressive sensing |
| spellingShingle | Huihuang Zhao Yaonan Wang Jinhua Zheng Zhijun Qiao Yun Zhang Solder joint image adaptive block compressive sensing with convex optimisation and Gini index The Journal of Engineering matrix algebra iterative methods data compression optimisation gradient methods surface mount technology image reconstruction compressed sensing solders image coding mechanical engineering computing ad_bcsgb_gini method solder joint image reconstruction performance comparing gini index convex optimisation problem square blocks novel adaptive block compressive sensing solder joint image compression surface mount technology components solder joint image adaptive block compressive sensing |
| title | Solder joint image adaptive block compressive sensing with convex optimisation and Gini index |
| title_full | Solder joint image adaptive block compressive sensing with convex optimisation and Gini index |
| title_fullStr | Solder joint image adaptive block compressive sensing with convex optimisation and Gini index |
| title_full_unstemmed | Solder joint image adaptive block compressive sensing with convex optimisation and Gini index |
| title_short | Solder joint image adaptive block compressive sensing with convex optimisation and Gini index |
| title_sort | solder joint image adaptive block compressive sensing with convex optimisation and gini index |
| topic | matrix algebra iterative methods data compression optimisation gradient methods surface mount technology image reconstruction compressed sensing solders image coding mechanical engineering computing ad_bcsgb_gini method solder joint image reconstruction performance comparing gini index convex optimisation problem square blocks novel adaptive block compressive sensing solder joint image compression surface mount technology components solder joint image adaptive block compressive sensing |
| url | https://digital-library.theiet.org/content/journals/10.1049/joe.2018.9148 |
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