An Energy-Efficient Compressive Image Coding for Green Internet of Things (IoT)
Aimed at a low-energy consumption of Green Internet of Things (IoT), this paper presents an energy-efficient compressive image coding scheme, which provides compressive encoder and real-time decoder according to Compressive Sensing (CS) theory. The compressive encoder adaptively measures each image...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-04-01
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| Series: | Sensors |
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| Online Access: | http://www.mdpi.com/1424-8220/18/4/1231 |
| _version_ | 1828137696616251392 |
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| author | Ran Li Xiaomeng Duan Xu Li Wei He Yanling Li |
| author_facet | Ran Li Xiaomeng Duan Xu Li Wei He Yanling Li |
| author_sort | Ran Li |
| collection | DOAJ |
| description | Aimed at a low-energy consumption of Green Internet of Things (IoT), this paper presents an energy-efficient compressive image coding scheme, which provides compressive encoder and real-time decoder according to Compressive Sensing (CS) theory. The compressive encoder adaptively measures each image block based on the block-based gradient field, which models the distribution of block sparse degree, and the real-time decoder linearly reconstructs each image block through a projection matrix, which is learned by Minimum Mean Square Error (MMSE) criterion. Both the encoder and decoder have a low computational complexity, so that they only consume a small amount of energy. Experimental results show that the proposed scheme not only has a low encoding and decoding complexity when compared with traditional methods, but it also provides good objective and subjective reconstruction qualities. In particular, it presents better time-distortion performance than JPEG. Therefore, the proposed compressive image coding is a potential energy-efficient scheme for Green IoT. |
| first_indexed | 2024-04-11T18:23:58Z |
| format | Article |
| id | doaj.art-2b10ea84700b49338f6be293cbef603d |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T18:23:58Z |
| publishDate | 2018-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-2b10ea84700b49338f6be293cbef603d2022-12-22T04:09:41ZengMDPI AGSensors1424-82202018-04-01184123110.3390/s18041231s18041231An Energy-Efficient Compressive Image Coding for Green Internet of Things (IoT)Ran Li0Xiaomeng Duan1Xu Li2Wei He3Yanling Li4School of Computer and Information Technology, Xinyang Normal University, Xinyang 464000, ChinaSchool of Computer and Information Technology, Xinyang Normal University, Xinyang 464000, ChinaSchool of Computer and Information Technology, Xinyang Normal University, Xinyang 464000, ChinaSchool of Computer and Information Technology, Xinyang Normal University, Xinyang 464000, ChinaSchool of Computer and Information Technology, Xinyang Normal University, Xinyang 464000, ChinaAimed at a low-energy consumption of Green Internet of Things (IoT), this paper presents an energy-efficient compressive image coding scheme, which provides compressive encoder and real-time decoder according to Compressive Sensing (CS) theory. The compressive encoder adaptively measures each image block based on the block-based gradient field, which models the distribution of block sparse degree, and the real-time decoder linearly reconstructs each image block through a projection matrix, which is learned by Minimum Mean Square Error (MMSE) criterion. Both the encoder and decoder have a low computational complexity, so that they only consume a small amount of energy. Experimental results show that the proposed scheme not only has a low encoding and decoding complexity when compared with traditional methods, but it also provides good objective and subjective reconstruction qualities. In particular, it presents better time-distortion performance than JPEG. Therefore, the proposed compressive image coding is a potential energy-efficient scheme for Green IoT.http://www.mdpi.com/1424-8220/18/4/1231Green IoTcompressive sensingimage codinggradient fieldlinear projection |
| spellingShingle | Ran Li Xiaomeng Duan Xu Li Wei He Yanling Li An Energy-Efficient Compressive Image Coding for Green Internet of Things (IoT) Sensors Green IoT compressive sensing image coding gradient field linear projection |
| title | An Energy-Efficient Compressive Image Coding for Green Internet of Things (IoT) |
| title_full | An Energy-Efficient Compressive Image Coding for Green Internet of Things (IoT) |
| title_fullStr | An Energy-Efficient Compressive Image Coding for Green Internet of Things (IoT) |
| title_full_unstemmed | An Energy-Efficient Compressive Image Coding for Green Internet of Things (IoT) |
| title_short | An Energy-Efficient Compressive Image Coding for Green Internet of Things (IoT) |
| title_sort | energy efficient compressive image coding for green internet of things iot |
| topic | Green IoT compressive sensing image coding gradient field linear projection |
| url | http://www.mdpi.com/1424-8220/18/4/1231 |
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