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Wireless image transfer by various antennas using transmitter and receiver modules at 5.8 GHz

Published online by Cambridge University Press:  21 October 2024

Gobind Rai ,
Puneet Sehgal  and
Kamlesh Patel Open the ORCID record for Kamlesh Patel [Opens in a new window]
Gobind Rai
Affiliation:
Department of Electronic Science, University of Delhi, New Delhi, India
Puneet Sehgal
Affiliation:
Department of Electronic Science, University of Delhi, New Delhi, India Atma Ram Sanatan Dharma College, University of Delhi, New Delhi, India
Kamlesh Patel*
Affiliation:
Department of Electronic Science, University of Delhi, New Delhi, India
*
Corresponding author: Kamlesh Patel; Email: [email protected]
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Abstract

This research proposes an inexpensive technique for wireless image transfer for security and surveillance applications. The technique uses a 5.8 GHz transmitter and receiver module, along with external antennas in the real-time image transfer within a radius of 100 m. The transferred images are stored in a laptop using a Python code-based graphical user interface application. Different antennas, dipole, circular split-ring resonators, hexagonal split-ring resonators, and metamaterial antennas are utilized for comparison. The Blind/Referenceless Image Spatial Quality Evaluator method is used to assess the picture quality of transferred images to quantify image transfer performance when no ground truth or reference photos are supplied. According to the presented results, images transferred using metamaterial antennas have higher quality than those transferred with other types of antennas. For security considerations, such a system can communicate and store the images in real time.

Keywords

Blind/Referenceless Image Spatial Quality Evaluator (BRISQUE)C-SRRgraphical user interfaceH-SRRimage quality scoremetamaterial antennaorthogonal frequency division multiple accessreal-time image transfertransmitter/receiver modulewireless sensor network
Type
Research Paper
Information
International Journal of Microwave and Wireless Technologies , Volume 16 , Issue 7 , September 2024 , pp. 1248 - 1259
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Copyright
© The Author(s), 2024. Published by Cambridge University Press in association with The European Microwave Association.

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References

Yang, Z, Liao, S and Cheng, W (2009) Joint power control and rate adaptation in wireless sensor networks. Ad Hoc Networks 7(2), 401–410.CrossRefGoogle Scholar
Yaghmaee, MH and Adjeroh, DA (2009) Priority-based rate control for service differentiation and congestion control in wireless multimedia sensor networks. Computer Networks 53, 1798–1811.CrossRefGoogle Scholar
Wu, H and Abouzeid, AA (2005) Energy efficient distributed image compression in resource-constrained multihop wireless networks. Computer Communications 28(14), 1658–1668.CrossRefGoogle Scholar
Zhang, W, Deng, Z, Wang, G, Wittenburg, L and Xing, Z (2002) Distributed problem-solving in sensor networks. In Proceedings of the First International Joint Conference on Autonomous Agents and Multiagent Systems, 988–989.CrossRefGoogle Scholar
Culurciello, E and Andreou, AG (2006) CMOS image sensors for sensor networks. Analog Integrated Circuits and Signal Processing 49, 39–51.CrossRefGoogle Scholar
Akyildiz, IF, Melodia, T and Chowdhury, KR (2007) A survey on wireless multimedia sensor networks. Computer Networks 51(4), 921–960.CrossRefGoogle Scholar
Ghorbel, O, Jabri, I, Ayedi, W and Abid, M (2011) Experimental study of compressed images transmission through WSN. In Microelectronics (ICM) 2011 International Conference, 1–6.CrossRefGoogle Scholar
Corcoran, PM, Bigioi, P and Steinberg, E (2001) Wireless transfer of images from a digital camera to the internet via a standard GSM mobile phone. IEEE Transactions on Consumer Electronics 47(3), 542–547.CrossRefGoogle Scholar
Eldin, HZ, Elhosseini, MA and Ali, HA (2015) Image compression algorithms in wireless multimedia sensor networks: A survey. Ain Shams Engineering Journal 6, 481–490.Google Scholar
Chandra, M, Agarwal, D and Bansae, A (2016) Image transmission through wireless channel: A review. In 1st IEEE International Conference on Power Electronics. Intelligent Control and Energy Systems (ICPEICES-2016).CrossRefGoogle Scholar
Eldokany, I, El-Rabaie, E-SM, Elhalafawy, SM, Zein Eldin, MA, Shahieen, MH, Soliman, NF, El-Bendary, MA, El-Naby, MA, Al-Kamali, FS, Elashry, IF and Abd El-Samie, FE (2015) Efficient transmission of encrypted images with OFDM in the presence of carrier frequency offset. Wireless personal Communications 84, 475–521.CrossRefGoogle Scholar
Zhang, J, Ma, X, Fu, X and Yang, J (2019) Sparse nonorthogonal wavelet division multiplexing for underwater sonar image transmission. IEEE Transactions on Vehicular Technology 68(12), 11806–11815.CrossRefGoogle Scholar
Bourtsoulatze, E, Kurka, DB and Gündüz, D (2019) Deep joint source-channel coding for wireless image transmission, IEEE Transactions on Cognitive Communications and Networking 5(3), 567–579.CrossRefGoogle Scholar
Dharavathu, K and Mosa, SA (2020) Efficient transmission of an encrypted image through a MIMO–OFDM system with different encryption schemes. Sensing and Imaging 21, .CrossRefGoogle Scholar
Eyssa, AA, Abdelsamie, FE and Abdelnaiem, AE (2020) An efficient image steganography approach over wireless communication system. Wireless Personal Communications 110, 321–337.CrossRefGoogle Scholar
Guo, Z and Liu, S (2021) Wireless image transmission interference signal recognition system based on deep learning. Wireless Communications and Mobile Computing 2021, .Google Scholar
Al–Kamali, FS, Al–Junaid, AF and Al–Shamri, MYH (2021) New image transmission schemes for DST–Based MC–CDMA system. Arabian Journal for Science and Engineering 46, 1465–1479.CrossRefGoogle Scholar
Smitha, N, Tarun, ES, Eswar, KS, Reddy, NTK and Nagendra, P (2022) Image transmission using USRP through LabVIEW. In 2022 IEEE North Karnataka Subsection Flagship International Conference (NKCon), Vijaypur, India, 1–6.Google Scholar
Dihin, RA, Alharan, AFH, Abdulameer, MH and Ali, NS (2022) Evaluation the performance of statistical and information-theoretic properties over FFT-OFDM. In 2022 5th International Conference on Engineering Technology and its Applications (IICETA), Al-Najaf, Iraq, 52–57.CrossRefGoogle Scholar
Zhang, Z, Yang, Q, He, S, Sun, M and Chen, J (2022) Wireless transmission of images with the assistance of multi-level semantic information. In 2022 International Symposium on Wireless Communication Systems (ISWCS), Zhejiang University, Zhejiang, China.CrossRefGoogle Scholar
Lokumarambage, MU, Gowrisetty, VSS, Rezaei, H, Sivalingam, T, Rajatheva, N and Fernando, A (2023) Wireless end-to-end image transmission system using semantic communications. IEEE Access 11, 37149–37163.CrossRefGoogle Scholar
Xie, B, Wu, Y, Ng, DWK and Zhang, W (2023) Communication-efficient framework for distributed image semantic wireless transmission. IEEE Internet of Things Journal 10(24), 22555–22568.CrossRefGoogle Scholar
Abduh, F, Al–Fahaidy, K, AL–Bouthigy, R, Yahya, M, Al–Shamri, H and Abdulkareem, S (2024) Secure image transmission through LTE wireless communications systems. EURASIP Journal on Image & Video Processing 2024, .Google Scholar
Norris, C and Armstrong, G (1999) The Maximum Surveillance Society: The Rise of CCTV. Oxford: Berg.Google Scholar
Min, H, Lee, SH, De Neve, W and Ro, YM (2013) Improved license plate recognition for low-resolution CCTV forensics by integrating sparse representation-based super-resolution. In Digital-Forensics and Watermarking. International Workshop on Digital Watermarking, LNCS8389, 452–462.Google Scholar
Kreis, R (2004) Issues of spectral quality in clinical H-magnetic resonance spectroscopy and a gallery of artifacts. NMR in Biomedicine 17(6), 361–381.CrossRefGoogle Scholar
Avcibas, I, Sankur, B and Sayood, K (2002) Statistical evaluation of image quality measures. Journal of Electronic Imaging 11(2), 206–223.Google Scholar
Farrell, JE (1999) Image quality evaluation. In MacDonald, LW and Luo, MR (eds), Colour Imaging: Vision and Technology. West Sussex: John Wiley & Sons Inc, 285–313.Google Scholar
Cadik, M and Slavik, P (2004) Evaluation of two principal approaches to objective image quality assessment. In 8th International Conference on Information Visualisation, IEEE Computer Society Press, 513–551.CrossRefGoogle Scholar
Nguyen, TB and Ziou, D (2000) Contextual and non-contextual performance evaluation of edge detectors. Pattern Recognition Letters 21(9), 805–816.CrossRefGoogle Scholar
Wang, Z, Sheikh, HR and Bovik, AC (2002) No-reference perceptual quality assessment of JPEG compressed images. In Proceedings. International Conference on Image Processing I.Google Scholar
Wang, Z, Bovik, AC, Sheikh, HR and Simoncelli, EP (2004) Image quality assessment: From error visibility to structural similarity. IEEE Transactions on Image Processing 13(4), 600–612.CrossRefGoogle ScholarPubMed
Kim, W, Nguyen, A-D, Lee, S and Bovik, AC (2020) Dynamic receptive field generation for full-reference image quality assessment. IEEE Transactions on Image Processing 29, 4219–4231.CrossRefGoogle Scholar
Golestaneh, S and Karam, LJ (2016) Reduced-reference quality assessment based on the entropy of DWT coefficients of locally weighted gradient magnitudes. IEEE Transactions on Image Processing 25(11), 5293–5303.Google ScholarPubMed
Wan, Z, Gu, K and Zhao, D (2020) Reduced reference stereoscopic image quality assessment using sparse representation and natural scene statistics. IEEE Transactions on Multimedia 22(8), 2024–2037.CrossRefGoogle Scholar
Choi, MG, Jung, JH and Jeon, JW (2009) No-reference image quality assessment using blur and noise. International Journal of Electronics and Electrical Engineering 3, 318–322.Google Scholar
Mittal, A and Bovik, AC (2012) No-reference image quality assessment in the spatial domain. IEEE Transactions on Image Processing 21(12), 4695–4708.CrossRefGoogle ScholarPubMed
Chawdhary, A, Kumari, S, Bhavsar, A and Verma, R (2018) No reference evaluation in super-resolution for CCTV footage. In IEEE 13th International Conference on Industrial and Information Systems (ICIIS).CrossRefGoogle Scholar
Moorthy, AK and Bovik, AC (2011) Blind image quality assessment: From natural scene statistics to perceptual quality. IEEE Transactions on Image Processing 20(12), 3350–3364.CrossRefGoogle ScholarPubMed
Yang, X, Li, F, Zhang, W and He, L (2018) Blind image quality assessment of natural scenes based on entropy differences in the DCT domain. Entropy 20(12), 885–906.CrossRefGoogle ScholarPubMed
Saad, MA, Bovik, AC and Charrier, C (2012) Blind image quality assessment: A natural scene statistics approach in the DCT domain. IEEE Transactions on Image Processing 21(8), 3339–3352.CrossRefGoogle ScholarPubMed
Yang, X, Li, F, Gu, K and Liu, H (2022) Study of natural scene categories in measurement of perceived image quality. IEEE Transactions on Instrumentation and Measurement 71, 1–12.Google Scholar
Shen, L, Zhao, B, Pan, Z, Peng, B, Kwong, S and Lei, J (2022) Channel recombination and projection network for blind image quality measurement. IEEE Transactions on Instrumentation and Measurement 71, 1–12.Google Scholar
Wang, X, Xiong, J and Lin, W (2023) Visual interaction perceptual network for blind image quality assessment. IEEE Transactions on Multimedia 25, 8958–8971.Google Scholar
Chen, J, Li, S, Lin, L, Wan, J and Li, Z (2023) No-reference blurred image quality assessment method based on structure of structure features. Signal Processing: Image Communication 118, .Google Scholar
Rajevenceltha, J and Gaidhane, VH (2023) A no-reference image quality assessment model based on neighborhood component analysis and Gaussian process. Journal of Visual Communication and Image Representation 98(11), .Google Scholar
Wei, X, Li, J, Zhou, M and Wang, X (2022) Contrastive distortion‐level learning‐based no‐reference image‐quality assessment. International Journal of Intelligent Systems 37, 8730–8746.CrossRefGoogle Scholar
Rajevenceltha, J and Gaidhane, VH (2022) An efficient approach for no-reference image quality assessment based on statistical texture and structural features. Engineering Science and Technology 30, .Google Scholar
Sehgal, P and Patel, K (2021) Performance analysis and impedance modeling of rectangular and circular split-ring resonator antennas in 2.4/5.2 GHz bands. Progress in Electromagnetics Research C 117, 159–171.CrossRefGoogle Scholar
Sehgal, P and Patel, K (2023) Dual-band hexagonal SRR antennas and their applications in SIMO and MISO-based WLAN/WiMAX systems. Progress in Electromagnetics Research B 99, 139–157.CrossRefGoogle Scholar
Yılmaz, HÖ and Yaman, F (2020) Metamaterial antenna designs for a 5.8-GHz Doppler radar. IEEE Transactions on Instrumentation and Measurement 69(4), 1775–1782.CrossRefGoogle Scholar