{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,6]],"date-time":"2025-08-06T12:37:41Z","timestamp":1754483861707},"reference-count":35,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2022,3,18]],"date-time":"2022-03-18T00:00:00Z","timestamp":1647561600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,3,18]],"date-time":"2022-03-18T00:00:00Z","timestamp":1647561600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Wireless Netw"],"published-print":{"date-parts":[[2024,7]]},"DOI":"10.1007\/s11276-022-02921-1","type":"journal-article","created":{"date-parts":[[2022,3,18]],"date-time":"2022-03-18T15:09:28Z","timestamp":1647616168000},"page":"4221-4235","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["An efficient adaptive compressive sensing technique for underwater image compression in IoUT"],"prefix":"10.1007","volume":"30","author":[{"given":"R.","family":"Monika","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Samiappan","family":"Dhanalakshmi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"R.","family":"Kumar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"R","family":"Narayanamoorthi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Khin Wee","family":"Lai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,3,18]]},"reference":[{"issue":"2","key":"2921_CR1","doi-asserted-by":"publisher","first-page":"584","DOI":"10.1016\/j.jnca.2011.10.015","volume":"35","author":"MC Domingo","year":"2012","unstructured":"Domingo, M. C. (2012). An overview of the internet of things for people with disabilities. Journal of Network and Computer Applications, 35(2), 584\u2013596.","journal-title":"Journal of Network and Computer Applications"},{"issue":"6","key":"2921_CR2","doi-asserted-by":"publisher","first-page":"1499","DOI":"10.1007\/s00371-020-01884-8","volume":"37","author":"R Monika","year":"2021","unstructured":"Monika, R., Samiappan, D., & Kumar, R. (2021). Underwater image compression using energy based adaptive block compressive sensing for IoUT applications. The Visual Computer, 37(6), 1499\u20131515.","journal-title":"The Visual Computer"},{"issue":"6","key":"2921_CR3","doi-asserted-by":"publisher","first-page":"2097","DOI":"10.1007\/s11554-019-00879-6","volume":"17","author":"N Krishnaraj","year":"2020","unstructured":"Krishnaraj, N., Elhoseny, M., Thenmozhi, M., Selim, M. M., & Shankar, K. (2020). Deep learning model for real-time image compression in Internet of Underwater Things (IoUT). Journal of Real-Time Image Processing, 17(6), 2097\u20132111.","journal-title":"Journal of Real-Time Image Processing"},{"key":"2921_CR4","doi-asserted-by":"publisher","first-page":"162925","DOI":"10.1016\/j.ijleo.2019.06.025","volume":"192","author":"A Mathias","year":"2019","unstructured":"Mathias, A., & Samiappan, D. (2019). Underwater image restoration based on diffraction bounded optimization algorithm with dark channel prior. Optik, 192, 162925.","journal-title":"Optik"},{"key":"2921_CR5","doi-asserted-by":"crossref","unstructured":"Aboubakar, M.,\u00a0Kellil, M., & Roux, P. (2021). A review of IoT network management: Current status and perspectives. Journal of King Saud University-Computer and Information Sciences.","DOI":"10.1016\/j.jksuci.2021.03.006"},{"issue":"12","key":"2921_CR6","doi-asserted-by":"publisher","first-page":"144","DOI":"10.1109\/MCOM.2012.6384464","volume":"50","author":"A Sehgal","year":"2012","unstructured":"Sehgal, A., Perelman, V., Kuryla, S., & Schonwalder, J. (2012). Management of resource constrained devices in the internet of things. IEEE Communications Magazine, 50(12), 144\u2013149.","journal-title":"IEEE Communications Magazine"},{"issue":"11","key":"2921_CR7","doi-asserted-by":"publisher","first-page":"6347","DOI":"10.1007\/s11042-015-2575-8","volume":"75","author":"S Fayed","year":"2016","unstructured":"Fayed, S., Youssef, S. M., El-Helw, A., Patwary, M., & Moniri, M. (2016). Adaptive compressive sensing for target tracking within wireless visual sensor networks-based surveillance applications. Multimedia Tools and Applications, 75(11), 6347\u20136371.","journal-title":"Multimedia Tools and Applications"},{"issue":"4","key":"2921_CR8","doi-asserted-by":"publisher","first-page":"45","DOI":"10.3390\/jsan7040045","volume":"7","author":"H Djelouat","year":"2018","unstructured":"Djelouat, H., Amira, A., & Bensaali, F. (2018). Compressive sensing-based IoT applications: A review. Journal of Sensor and Actuator Networks, 7(4), 45.","journal-title":"Journal of Sensor and Actuator Networks"},{"key":"2921_CR9","first-page":"115774","volume":"82","author":"H Fu","year":"2020","unstructured":"Fu, H., Liang, F., Lei, B., Bian, N., Zhang, Q., Akbari, M., Liang, J., & Tu, C. (2020). Improved hybrid layered image compression using deep learning and traditional codecs. Signal Processing: Image Communication, 82, 115774.","journal-title":"Signal Processing: Image Communication"},{"key":"2921_CR10","first-page":"60","volume":"69","author":"J Ling","year":"2018","unstructured":"Ling, J., Zhang, K., Zhang, Y., Yang, D., & Chen, Z. (2018). A saliency prediction model on 360 degree images using color dictionary based sparse representation. Signal Processing: Image Communication, 69, 60\u201368.","journal-title":"Signal Processing: Image Communication"},{"issue":"1","key":"2921_CR11","doi-asserted-by":"publisher","first-page":"117","DOI":"10.1007\/s00371-016-1318-9","volume":"34","author":"Z Zha","year":"2018","unstructured":"Zha, Z., Liu, X., Zhang, X., Chen, Y., Tang, L., Bai, Y., Wang, Q., & Shang, Z. (2018). Compressed sensing image reconstruction via adaptive sparse nonlocal regularization. The Visual Computer, 34(1), 117\u2013137.","journal-title":"The Visual Computer"},{"issue":"4","key":"2921_CR12","doi-asserted-by":"publisher","first-page":"1289","DOI":"10.1109\/TIT.2006.871582","volume":"52","author":"DL Donoho","year":"2006","unstructured":"Donoho, D. L. (2006). Compressed sensing. IEEE Transactions on information theory, 52(4), 1289\u20131306.","journal-title":"IEEE Transactions on information theory"},{"key":"2921_CR13","doi-asserted-by":"crossref","unstructured":"Eldar, Y. C., & Kutyniok, G. (2012). Compressed sensing: Theory and applications. Cambridge University Press.","DOI":"10.1017\/CBO9780511794308"},{"key":"2921_CR14","unstructured":"Gan, L. (2007). Block compressed sensing of natural images. In 2007 15th International conference on digital signal processing, IEEE (pp. 403\u2013406)."},{"key":"2921_CR15","doi-asserted-by":"crossref","unstructured":"Gao, X., Zhang, J., Che, W., Fan, X., & Zhao, D. (2015). Block-based compressive sensing coding of natural images by local structural measurement matrix. In Data Compression Conference, IEEE, (pp. 133\u2013142).","DOI":"10.1109\/DCC.2015.47"},{"key":"2921_CR16","doi-asserted-by":"crossref","unstructured":"Monika, R., Dhanalakshmi, S., & Sreejith, S. (2018). Coefficient random permutation based compressed sensing for medical image compression. Advances in Electronics, Communication and Computing (pp. 529\u2013536). Springer.","DOI":"10.1007\/978-981-10-4765-7_56"},{"key":"2921_CR17","doi-asserted-by":"crossref","unstructured":"Zhu, S., Zeng, B., & Gabbouj, M., (2014). Adaptive reweighted compressed sensing for image compression. In 2014 IEEE International Symposium on Circuits and Systems (ISCAS), IEEE, (pp. 1\u20134).","DOI":"10.1109\/ISCAS.2014.6865050"},{"issue":"7","key":"2921_CR18","doi-asserted-by":"publisher","first-page":"885","DOI":"10.1016\/j.jvcir.2013.06.006","volume":"24","author":"Z Gao","year":"2013","unstructured":"Gao, Z., Xiong, C., Ding, L., & Zhou, C. (2013). Image representation using block compressive sensing for compression applications. Journal of Visual Communication and Image Representation, 24(7), 885\u2013894.","journal-title":"Journal of Visual Communication and Image Representation"},{"issue":"1","key":"2921_CR19","doi-asserted-by":"publisher","first-page":"776","DOI":"10.1109\/JSEN.2021.3130947","volume":"22","author":"R Monika","year":"2021","unstructured":"Monika, R., Dhanalakshmi, S., Kumar, R., & Narayanamoorthi, R. (2021). Coefficient permuted adaptive block compressed sensing for camera enabled underwater wireless sensor nodes. IEEE Sensors Journal, 22(1), 776\u2013784.","journal-title":"IEEE Sensors Journal"},{"issue":"3","key":"2921_CR20","doi-asserted-by":"publisher","first-page":"4227","DOI":"10.1007\/s11042-016-3496-x","volume":"76","author":"J Zhang","year":"2017","unstructured":"Zhang, J., Xiang, Q., Yin, Y., Chen, C., & Luo, X. (2017). Adaptive compressed sensing for wireless image sensor networks. Multimedia Tools and Applications, 76(3), 4227\u20134242.","journal-title":"Multimedia Tools and Applications"},{"issue":"6","key":"2921_CR21","doi-asserted-by":"publisher","first-page":"155014771878175","DOI":"10.1177\/1550147718781751","volume":"14","author":"R Li","year":"2018","unstructured":"Li, R., Duan, X., & Lv, Y. (2018). Adaptive compressive sensing of images using error between blocks. International Journal of Distributed Sensor Networks, 14(6), 1550147718781751.","journal-title":"International Journal of Distributed Sensor Networks"},{"key":"2921_CR22","doi-asserted-by":"crossref","unstructured":"Sun, F.,\u00a0Xiao, D.,\u00a0He, W.,\u00a0Li, R. (2017). Adaptive image compressive sensing using texture contrast. International Journal of Digital Multimedia Broadcasting, 2017.","DOI":"10.1155\/2017\/3902543"},{"key":"2921_CR23","doi-asserted-by":"crossref","unstructured":"Li, R.,\u00a0Duan, X.,\u00a0Guo, X.,\u00a0He, W., & Lv, Y. (2017). Adaptive compressive sensing of images using spatial entropy. Computational intelligence and neuroscience, 2017.","DOI":"10.1155\/2017\/9059204"},{"issue":"6","key":"2921_CR24","doi-asserted-by":"publisher","first-page":"1702","DOI":"10.1587\/transinf.2015EDL8230","volume":"99","author":"J Xu","year":"2016","unstructured":"Xu, J., Qiao, Y., & Fu, Z. (2016). Adaptive perceptual block compressive sensing for image compression. IEICE Transactions on Information and Systems, 99(6), 1702\u20131706.","journal-title":"IEICE Transactions on Information and Systems"},{"key":"2921_CR25","doi-asserted-by":"crossref","unstructured":"Wang, F.,\u00a0Zhang, A.,\u00a0Li, J., & Li, S. (2012). Perceptual compressive sensing scheme based on human vision system. In 2012 IEEE\/ACIS 11th International Conference on Computer and Information Science, IEEE (pp. 351\u2013355).","DOI":"10.1109\/ICIS.2012.83"},{"issue":"11","key":"2921_CR26","doi-asserted-by":"publisher","first-page":"973","DOI":"10.1109\/LSP.2010.2080673","volume":"17","author":"Y Yu","year":"2010","unstructured":"Yu, Y., Wang, B., & Zhang, L. (2010). Saliency-based compressive sampling for image signals. IEEE Signal Processing Letters, 17(11), 973\u2013976.","journal-title":"IEEE Signal Processing Letters"},{"issue":"21","key":"2921_CR27","doi-asserted-by":"publisher","first-page":"14777","DOI":"10.1007\/s11042-018-7062-6","volume":"79","author":"Z Zhang","year":"2020","unstructured":"Zhang, Z., Bi, H., Kong, X., Li, N., & Lu, D. (2020). Adaptive compressed sensing of color images based on salient region detection. Multimedia Tools and Applications, 79(21), 14777\u201314791.","journal-title":"Multimedia Tools and Applications"},{"issue":"1","key":"2921_CR28","doi-asserted-by":"publisher","first-page":"537","DOI":"10.1007\/s11042-017-5249-x","volume":"78","author":"S Zhou","year":"2019","unstructured":"Zhou, S., Chen, Z., Zhong, Q., & Li, H. (2019). Block compressed sampling of image signals by saliency based adaptive partitioning. Multimedia Tools and Applications, 78(1), 537\u2013553.","journal-title":"Multimedia Tools and Applications"},{"issue":"5","key":"2921_CR29","first-page":"647","volume":"7","author":"A Bhardwaj","year":"2009","unstructured":"Bhardwaj, A., & Ali, R. (2009). Image compression using modified fast haar wavelet transform. World Applied Sciences Journal, 7(5), 647\u2013653.","journal-title":"World Applied Sciences Journal"},{"issue":"11","key":"2921_CR30","doi-asserted-by":"publisher","first-page":"7266","DOI":"10.1016\/j.jfranklin.2020.04.022","volume":"357","author":"AB Abubakar","year":"2020","unstructured":"Abubakar, A. B., Kumam, P., Mohammad, H., & Awwal, A. M. (2020). A barzilai-borwein gradient projection method for sparse signal and blurred image restoration. Journal of the Franklin Institute, 357(11), 7266\u20137285.","journal-title":"Journal of the Franklin Institute"},{"key":"2921_CR31","doi-asserted-by":"publisher","first-page":"124965124965","DOI":"10.1016\/j.amc.2019.124965","volume":"371","author":"F Tong","year":"2020","unstructured":"Tong, F., Li, L., Peng, H., & Yang, Y. (2020). An effective algorithm for the spark of sparse binary measurement matrices. Applied Mathematics and Computation, 371, 124965124965.","journal-title":"Applied Mathematics and Computation"},{"issue":"6","key":"2921_CR32","doi-asserted-by":"publisher","first-page":"1468","DOI":"10.1109\/TCSI.2017.2648854","volume":"64","author":"A Kulkarni","year":"2017","unstructured":"Kulkarni, A., & Mohsenin, T. (2017). Low overhead architectures for OMP compressive sensing reconstruction algorithm. IEEE Transactions on Circuits and Systems I: Regular Papers, 64(6), 1468\u20131480.","journal-title":"IEEE Transactions on Circuits and Systems I: Regular Papers"},{"key":"2921_CR33","doi-asserted-by":"crossref","unstructured":"Hore, A., & Ziou, D. (2010). Image quality metrics: Psnr vs. ssim. In 2010 20th International Conference on Pattern Recognition, IEEE (pp. 2366\u20132369).","DOI":"10.1109\/ICPR.2010.579"},{"issue":"3","key":"2921_CR34","first-page":"29","volume":"7","author":"KV Thakur","year":"2016","unstructured":"Thakur, K. V., Damodare, O. H., & Sapkal, A. M. (2016). Identification of suited quality metrics for natural and medical images. Signal and Image Processing: An International Journal (SIPIJ), 7(3), 29\u201343.","journal-title":"Signal and Image Processing : An International Journal (SIPIJ)"},{"key":"2921_CR35","unstructured":"xahidbuffon. (2019). Underwater-Datasets, https:\/\/github.com\/xahidbuffon\/Underwater-Datasets\/commits?author=xahidbuffon, [Online; accessed 20-Sep-2021]."}],"container-title":["Wireless Networks"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11276-022-02921-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11276-022-02921-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11276-022-02921-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,3]],"date-time":"2024-07-03T15:54:00Z","timestamp":1720022040000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11276-022-02921-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3,18]]},"references-count":35,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2024,7]]}},"alternative-id":["2921"],"URL":"https:\/\/doi.org\/10.1007\/s11276-022-02921-1","relation":{},"ISSN":["1022-0038","1572-8196"],"issn-type":[{"value":"1022-0038","type":"print"},{"value":"1572-8196","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,3,18]]},"assertion":[{"value":"7 February 2022","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 March 2022","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}