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Singh, R., Ashok, A., & Saraswat, M. (2020). Optimised robust watermarking technique using CKGSA in DCT-SVD domain. IET Image Processing, 14(10), 2052–2063.SinghR.AshokA.SaraswatM.2020Optimised robust watermarking technique using CKGSA in DCT-SVD domainIET Image Processing141020522063Search in Google Scholar
Bhardwaj, C., & Urvashi, S. M. (2017). Implementation and performance assessment of compressed sensing for images and video signals. Journal of Global Pharma Technology, 6(9), 123–133.BhardwajC.UrvashiS. M.2017Implementation and performance assessment of compressed sensing for images and video signalsJournal of Global Pharma Technology69123133Search in Google Scholar
He, Y., & Hu, Y. (2018, May). A proposed digital image watermarking based on DWT-DCT-SVD. In 2018 2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC) (pp. 1214–1218). IEEE.HeY.HuY.2018, MayA proposed digital image watermarking based on DWT-DCT-SVDIn2018 2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC)12141218IEEESearch in Google Scholar
Bhardwaj, C., Sharma, U., Jain, S., & Sood, M. (2019). Implementation and Performance Assessment of Biomedical Image Compression and Reconstruction Algorithms for Telemedicine Applications: Compressive Sensing for Biomedical Images. In Medical Data Security for Bioengineers (pp. 52–80). IGI Global.BhardwajC.SharmaU.JainS.SoodM.2019Implementation and Performance Assessment of Biomedical Image Compression and Reconstruction Algorithms for Telemedicine Applications: Compressive Sensing for Biomedical ImagesIn Medical Data Security for Bioengineers5280IGI GlobalSearch in Google Scholar
Zear, A., & Singh, P. K. (2022). Secure and robust color image dual watermarking based on LWT-DCT-SVD. Multimedia Tools and Applications, 81(19), 26721–26738.ZearA.SinghP. K.2022Secure and robust color image dual watermarking based on LWT-DCT-SVDMultimedia Tools and Applications81192672126738Search in Google Scholar
Awasthi, D., & Srivastava, V. K. (2022). LWT-DCT-SVD and DWT-DCT-SVD based watermarking schemes with their performance enhancement using Jaya and Particle swarm optimization and comparison of results under various attacks. Multimedia Tools and Applications, 81(18), 25075–25099.AwasthiD.SrivastavaV. K.2022LWT-DCT-SVD and DWT-DCT-SVD based watermarking schemes with their performance enhancement using Jaya and Particle swarm optimization and comparison of results under various attacksMultimedia Tools and Applications81182507525099Search in Google Scholar
Novamizanti, L., Wahidah, I., & Dhea Prameiswari Wardana, N. P. (2020). A Robust Medical Images Watermarking Using FDCuT-DCT-SVD. International Journal of Intelligent Engineering & Systems, 13(6).NovamizantiL.WahidahI.Dhea Prameiswari WardanaN. P.2020A Robust Medical Images Watermarking Using FDCuT-DCT-SVDInternational Journal of Intelligent Engineering & Systems136Search in Google Scholar
Ernawan, F., Ramalingam, M., Sadiq, A. S., & Mustaffa, Z. (2017). An improved imperceptibility and robustness of 4 × 4 DCT-SVD image watermarking with a modified entropy. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 9(2–7), 111–116.ErnawanF.RamalingamM.SadiqA. S.MustaffaZ.2017An improved imperceptibility and robustness of 4 × 4 DCT-SVD image watermarking with a modified entropyJournal of Telecommunication, Electronic and Computer Engineering (JTEC)92–7111116Search in Google Scholar
Kanhe, A., & Gnanasekaran, A. (2018). Robust image-in-audio watermarking technique based on DCT-SVD transform. EURASIP Journal on Audio, Speech, and Music Processing, 2018(1), 1–12.KanheA.GnanasekaranA.2018Robust image-in-audio watermarking technique based on DCT-SVD transformEURASIP Journal on Audio, Speech, and Music Processing20181112Search in Google Scholar
Mokashi, B., Bhat, V. S., Pujari, J. D., Roopashree, S., Mahesh, T. R., & Alex, D. S. (2022). Efficient Hybrid Blind Watermarking in DWT-DCT-SVD with Dual Biometric Features for Images. Contrast Media & Molecular Imaging, 2022.MokashiB.BhatV. S.PujariJ. D.RoopashreeS.MaheshT. R.AlexD. S.2022Efficient Hybrid Blind Watermarking in DWT-DCT-SVD with Dual Biometric Features for ImagesContrast Media & Molecular Imaging2022Search in Google Scholar
Rippel, O., & Bourdev, L. (2017, July). Real-time adaptive image compression. In International Conference on Machine Learning (pp. 2922–2930). PMLR.RippelO.BourdevL.2017, JulyReal-time adaptive image compressionInInternational Conference on Machine Learning29222930PMLRSearch in Google Scholar
Gan, Z., Chai, X., Bi, J., & Chen, X. (2022). Content-adaptive image compression and encryption via optimized compressive sensing with double random phase encoding driven by chaos. Complex & Intelligent Systems, 8(3), 2291–2309.GanZ.ChaiX.BiJ.ChenX.2022Content-adaptive image compression and encryption via optimized compressive sensing with double random phase encoding driven by chaosComplex & Intelligent Systems8322912309Search in Google Scholar
Liu, H., Yuan, H., Liu, Q., Hou, J., Zeng, H., & Kwong, S. (2021). A hybrid compression framework for color attributes of static 3D point clouds. IEEE Transactions on Circuits and Systems for Video Technology, 32(3), 1564–1577.LiuH.YuanH.LiuQ.HouJ.ZengH.KwongS.2021A hybrid compression framework for color attributes of static 3D point cloudsIEEE Transactions on Circuits and Systems for Video Technology32315641577Search in Google Scholar
Jifara, W., Jiang, F., Rho, S., Cheng, M., & Liu, S. (2019). Medical image denoising using convolutional neural network: a residual learning approach. The Journal of Supercomputing, 75, 704–718.JifaraW.JiangF.RhoS.ChengM.LiuS.2019Medical image denoising using convolutional neural network: a residual learning approachThe Journal of Supercomputing75704718Search in Google Scholar
Zamir, S. W., Arora, A., Khan, S., Hayat, M., Khan, F. S., Yang, M. H., & Shao, L. (2021). Multi-stage progressive image restoration. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition (pp. 14821–14831).ZamirS. W.AroraA.KhanS.HayatM.KhanF. S.YangM. H.ShaoL.2021Multi-stage progressive image restorationInProceedings of the IEEE/CVF conference on computer vision and pattern recognition1482114831Search in Google Scholar
He, Z., Li, H., Wang, Z., Xia, S., & Zhu, W. (2021). Adaptive compression for online computer vision: An edge reinforcement learning approach. ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), 17(4), 1–23.HeZ.LiH.WangZ.XiaS.ZhuW.2021Adaptive compression for online computer vision: An edge reinforcement learning approachACM Transactions on Multimedia Computing, Communications, and Applications (TOMM)174123Search in Google Scholar
Bai, Y., Yang, X., Liu, X., Jiang, J., Wang, Y., Ji, X., & Gao, W. (2022, June). Towards end-to-end image compression and analysis with transformers. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 36, No. 1, pp. 104–112).BaiY.YangX.LiuX.JiangJ.WangY.JiX.GaoW.2022, JuneTowards end-to-end image compression and analysis with transformersInProceedings of the AAAI Conference on Artificial Intelligence361104112Search in Google Scholar
Cao, F., Guo, D., Wang, T., Yao, H., Li, J., & Qin, C. (2023). Universal screen-shooting robust image watermarking with channel-attention in DCT domain. Expert Systems with Applications, 238, 122062.CaoF.GuoD.WangT.YaoH.LiJ.QinC.2023Universal screen-shooting robust image watermarking with channel-attention in DCT domainExpert Systems with Applications238122062Search in Google Scholar
Kanagaraj, H., & Muneeswaran, V. (2020, March). Image compression using HAAR discrete wavelet transform. In 2020 5th International Conference on Devices, Circuits and Systems (ICDCS) (pp. 271–274). IEEE.KanagarajH.MuneeswaranV.2020, MarchImage compression using HAAR discrete wavelet transformIn2020 5th International Conference on Devices, Circuits and Systems (ICDCS)271274IEEESearch in Google Scholar
Liu, X., An, P., Chen, Y., & Huang, X. (2022). An improved lossless image compression algorithm based on Huffman coding. Multimedia Tools and Applications, 81(4), 4781–4795.LiuX.AnP.ChenY.HuangX.2022An improved lossless image compression algorithm based on Huffman codingMultimedia Tools and Applications81447814795Search in Google Scholar
Lee, J. H., Gwon, G. H., Kim, I. H., & Jung, H. J. (2023). A Motion Deblurring Network for Enhancing UAV Image Quality in Bridge Inspection. Drones, 7(11), 657.LeeJ. H.GwonG. H.KimI. H.JungH. J.2023A Motion Deblurring Network for Enhancing UAV Image Quality in Bridge InspectionDrones711657Search in Google Scholar
Garg, G., & Kumar, R. (2022). Analysis of image types, compression techniques and performance assessment metrics: A review. Journal of Information and Optimization Sciences, 43(3), 429–436.GargG.KumarR.2022Analysis of image types, compression techniques and performance assessment metrics: A reviewJournal of Information and Optimization Sciences433429436Search in Google Scholar
Abdulrahman, A. K., & Ozturk, S. (2019). A novel hybrid DCT and DWT based robust watermarking algorithm for color images. Multimedia Tools and Applications, 78, 17027–17049.AbdulrahmanA. K.OzturkS.2019A novel hybrid DCT and DWT based robust watermarking algorithm for color imagesMultimedia Tools and Applications781702717049Search in Google Scholar
Yeganegi, F., Hassanzade, V., & Ahadi, S. M. (2018, May). Comparative performance evaluation of SVD-based image compression. In Electrical Engineering (ICEE), Iranian Conference on (pp. 464–469). IEEE.YeganegiF.HassanzadeV.AhadiS. M.2018, MayComparative performance evaluation of SVD-based image compressionInElectrical Engineering (ICEE), Iranian Conference on464469IEEESearch in Google Scholar
Cui, Y., Liu, Z., Yao, W., Li, Q., Chan, A. B., Kuo, T. W., & Xue, C. J. (2020). Fully Nested Neural Network for Adaptive Compression and Quantization. In IJCAI (pp. 2080–2087).CuiY.LiuZ.YaoW.LiQ.ChanA. B.KuoT. W.XueC. J.2020Fully Nested Neural Network for Adaptive Compression and QuantizationInIJCAI20802087Search in Google Scholar
Chen, Y. K., Yang, S. W., Ndiour, I. J., Liao, Y., Somayazulu, V. S., Tickoo, O., & Varadarajan, S. (2020). U.S. Patent No. 10,742,399. Washington, DC: U.S. Patent and Trademark Office.ChenY. K.YangS. W.NdiourI. J.LiaoY.SomayazuluV. S.TickooO.VaradarajanS.2020U.S. Patent No. 10,742,399Washington, DCU.S. Patent and Trademark OfficeSearch in Google Scholar
Alseelawi, N., Hazim, H. T., & Salim ALRikabi, H. T. (2022). A Novel Method of Multimodal Medical Image Fusion Based on Hybrid Approach of NSCT and DTCWT. International Journal of Online & Biomedical Engineering, 18(3).AlseelawiN.HazimH. T.Salim ALRikabiH. T.2022A Novel Method of Multimodal Medical Image Fusion Based on Hybrid Approach of NSCT and DTCWTInternational Journal of Online & Biomedical Engineering183Search in Google Scholar
Nandeesha, R., & Somashekar, K. (2023). Content-Based Image Compression Using Hybrid Discrete Wavelet Transform with Block Vector Quantization. International Journal of Intelligent Systems and Applications in Engineering, 11(5s), 19–37.NandeeshaR.SomashekarK.2023Content-Based Image Compression Using Hybrid Discrete Wavelet Transform with Block Vector QuantizationInternational Journal of Intelligent Systems and Applications in Engineering115s1937Search in Google Scholar
Lu, Y., Gong, M., Huang, Z., Zhang, J., Chai, X., & Zhou, C. (2022). Exploiting compressed sensing (CS) and RNA operations for effective content-adaptive image compression and encryption. Optik, 263, 169357.LuY.GongM.HuangZ.ZhangJ.ChaiX.ZhouC.2022Exploiting compressed sensing (CS) and RNA operations for effective content-adaptive image compression and encryptionOptik263169357Search in Google Scholar
Akbari, M., Liang, J., Han, J., & Tu, C. (2021). Learned multi-resolution variable-rate image compression with octave-based residual blocks. IEEE Transactions on Multimedia, 23, 3013–3021.AkbariM.LiangJ.HanJ.TuC.2021Learned multi-resolution variable-rate image compression with octave-based residual blocksIEEE Transactions on Multimedia2330133021Search in Google Scholar
Sun, X. X., Pan, J. S., Weng, S., Hu, C. C., & Chu, S. C. (2023). Optimization of MSFs for watermarking using DWT-DCT-SVD and fish migration optimization with QUATRE. Multimedia Tools and Applications, 82(2), 2255–2276.SunX. X.PanJ. S.WengS.HuC. C.ChuS. C.2023Optimization of MSFs for watermarking using DWT-DCT-SVD and fish migration optimization with QUATREMultimedia Tools and Applications82222552276Search in Google Scholar
Klein, S. T., Saadia, S., & Shapira, D. (2021). Forward looking Huffman coding. Theory of Computing Systems, 65, 593–612.KleinS. T.SaadiaS.ShapiraD.2021Forward looking Huffman codingTheory of Computing Systems65593612Search in Google Scholar
Ahmad, I., Choi, W., & Shin, S. (2023). Comprehensive Analysis of Compressible Perceptual Encryption Methods—Compression and Encryption Perspectives. Sensors, 23(8), 4057.AhmadI.ChoiW.ShinS.2023Comprehensive Analysis of Compressible Perceptual Encryption Methods—Compression and Encryption PerspectivesSensors2384057Search in Google Scholar
Dimililer, K. (2022). DCT-based medical image compression using machine learning. Signal, Image and Video Processing, 16(1), 55–62.DimililerK.2022DCT-based medical image compression using machine learningSignal, Image and Video Processing1615562Search in Google Scholar
Farghaly, S. H., & Ismail, S. M. (2020). Floating-point discrete wavelet transform-based image compression on FPGA. AEU-International Journal of Electronics and Communications, 124, 153363.FarghalyS. H.IsmailS. M.2020Floating-point discrete wavelet transform-based image compression on FPGAAEU-International Journal of Electronics and Communications124153363Search in Google Scholar
Liu, Z., Wang, H., & Su, T. (2022, October). Learned Image Compression with Multi-Scale Spatial and Contextual Information Fusion. In 2022 IEEE International Conference on Image Processing (ICIP) (pp. 706–710). IEEE.LiuZ.WangH.SuT.2022, OctoberLearned Image Compression with Multi-Scale Spatial and Contextual Information FusionIn2022 IEEE International Conference on Image Processing (ICIP)706710IEEESearch in Google Scholar
Samkari, E., Arif, M., Alghamdi, M., & Al Ghamdi, M. A. (2023). Human Pose Estimation Using Deep Learning: A Systematic Literature Review. Machine Learning and Knowledge Extraction, 5(4), 1612–1659.SamkariE.ArifM.AlghamdiM.Al GhamdiM. A.2023Human Pose Estimation Using Deep Learning: A Systematic Literature ReviewMachine Learning and Knowledge Extraction5416121659Search in Google Scholar