Compressed Adaptive-Sampling-Rate Image Sensing Based on Overcomplete Dictionary
In this paper, a compressed adaptive image-sensing method based on an overcomplete ridgelet dictionary is proposed. Some low-complexity operations are designed to distinguish between smooth blocks and texture blocks in the compressed domain, and adaptive sampling is performed by assigning different...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-06-01
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| Series: | Entropy |
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| Online Access: | https://www.mdpi.com/1099-4300/27/7/709 |
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| author | Jianming Wang Dingpeng Li Qingqing Yang Yi Peng |
| author_facet | Jianming Wang Dingpeng Li Qingqing Yang Yi Peng |
| author_sort | Jianming Wang |
| collection | DOAJ |
| description | In this paper, a compressed adaptive image-sensing method based on an overcomplete ridgelet dictionary is proposed. Some low-complexity operations are designed to distinguish between smooth blocks and texture blocks in the compressed domain, and adaptive sampling is performed by assigning different sampling rates to different types of blocks. The efficient, sparse representation of images is achieved by using an overcomplete ridgelet dictionary; at the same time, a reasonable dictionary-partitioning method is designed, which effectively reduces the number of candidate dictionary atoms and greatly improves the speed of classification. Unlike existing methods, the proposed method does not rely on the original signal, and computation is simple, making it particularly suitable for scenarios where a device’s computing power is limited. At the same time, the proposed method can accurately identify smooth image blocks and more reasonably allocate sampling rates to obtain a reconstructed image with better quality. The experimental results show that our method’s image reconstruction quality is superior to that of existing ARCS methods and still maintains low computational complexity. |
| format | Article |
| id | doaj-art-c2fcd50826cf46a082f21a13459b8963 |
| institution | Kabale University |
| issn | 1099-4300 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj-art-c2fcd50826cf46a082f21a13459b89632025-08-20T03:36:14ZengMDPI AGEntropy1099-43002025-06-0127770910.3390/e27070709Compressed Adaptive-Sampling-Rate Image Sensing Based on Overcomplete DictionaryJianming Wang0Dingpeng Li1Qingqing Yang2Yi Peng3School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, ChinaSchool of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, ChinaSchool of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, ChinaSchool of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, ChinaIn this paper, a compressed adaptive image-sensing method based on an overcomplete ridgelet dictionary is proposed. Some low-complexity operations are designed to distinguish between smooth blocks and texture blocks in the compressed domain, and adaptive sampling is performed by assigning different sampling rates to different types of blocks. The efficient, sparse representation of images is achieved by using an overcomplete ridgelet dictionary; at the same time, a reasonable dictionary-partitioning method is designed, which effectively reduces the number of candidate dictionary atoms and greatly improves the speed of classification. Unlike existing methods, the proposed method does not rely on the original signal, and computation is simple, making it particularly suitable for scenarios where a device’s computing power is limited. At the same time, the proposed method can accurately identify smooth image blocks and more reasonably allocate sampling rates to obtain a reconstructed image with better quality. The experimental results show that our method’s image reconstruction quality is superior to that of existing ARCS methods and still maintains low computational complexity.https://www.mdpi.com/1099-4300/27/7/709compressed sensingovercomplete ridgelet dictionaryadaptive sampling ratewireless sensor image capture networks |
| spellingShingle | Jianming Wang Dingpeng Li Qingqing Yang Yi Peng Compressed Adaptive-Sampling-Rate Image Sensing Based on Overcomplete Dictionary Entropy compressed sensing overcomplete ridgelet dictionary adaptive sampling rate wireless sensor image capture networks |
| title | Compressed Adaptive-Sampling-Rate Image Sensing Based on Overcomplete Dictionary |
| title_full | Compressed Adaptive-Sampling-Rate Image Sensing Based on Overcomplete Dictionary |
| title_fullStr | Compressed Adaptive-Sampling-Rate Image Sensing Based on Overcomplete Dictionary |
| title_full_unstemmed | Compressed Adaptive-Sampling-Rate Image Sensing Based on Overcomplete Dictionary |
| title_short | Compressed Adaptive-Sampling-Rate Image Sensing Based on Overcomplete Dictionary |
| title_sort | compressed adaptive sampling rate image sensing based on overcomplete dictionary |
| topic | compressed sensing overcomplete ridgelet dictionary adaptive sampling rate wireless sensor image capture networks |
| url | https://www.mdpi.com/1099-4300/27/7/709 |
| work_keys_str_mv | AT jianmingwang compressedadaptivesamplingrateimagesensingbasedonovercompletedictionary AT dingpengli compressedadaptivesamplingrateimagesensingbasedonovercompletedictionary AT qingqingyang compressedadaptivesamplingrateimagesensingbasedonovercompletedictionary AT yipeng compressedadaptivesamplingrateimagesensingbasedonovercompletedictionary |