Abstract
In the recent years, video transmission area endures several failures owing to the limited amount of a cutting edge technique to store large sized videos. For this reason, video compression method is used. For compression of videos, frame formation can be done by splitting the video frames by A_Frames, B_Frames and C_Frames. These frames will stay unchanged entire process; it will also utilize the memory for computational purpose. The proposed work consists of 2 phases. In the first phase, Acclimatize Frame Formation (AFF) is used to expand the characteristic of video coding and EWNS linear transformation (ELT) is initiated for substituting B_Frames with neither A_Frame nor C_Frame. In the second phase, un-repetition simulated contrary based resurgence procedure (URSCRP) is proposed for restoration of videos that demonstrates tiny convolution and time necessity together with conservation of restoration feature. Simulation results shows that URSCRP provides better accuracy and optimization compared to other related procedures. URSCRP provides PSNR of 30 dB, accuracy of 98% and minimized amount of elapsed time compared to related procedures.
Similar content being viewed by others
Change history
20 September 2022
This article has been retracted. Please see the Retraction Notice for more detail: https://doi.org/10.1007/s11042-022-13971-0
References
Aghamaleki JA, Behrad A (2016) Inter-frame video forgery detection and localization using intrinsic effects of double compression on quantization errors of video coding. Signal Process Image Commun 47:289–302
Ahmadi A, Pouladi F, Salehinejad H, Talebi S (2011) Fast two-stage global motion estimation: a blocks and pixels sampling approach. Intelligent interactive multimedia systems and services 11:143–151
Candes E (2008) The restricted isometry property and its implications. Journal Comptes Rendus Mathematique 346(9–10):589–592
Donoho DL, Tsaig Y, Drori I, Starck J-L (2012) Sparse solution of underdetermined linear equations by stagewise orthogonal matching pursuit (StOMP). IEEE Trans Inf Theory 58(2):1094–1121
Drori I (2008) Compressed video sensing. In BMVA symposium on 3D video—Analysis, display, and applications
Fazel M, Candes E, Recht B, Parrilo P (2007). Compressed sensing and robust recovery of low rank matrices. In 42nd Asilomar conference on signals, systems and computers (pp. 1043–1047). October 26–29, 2008
Kumar V, Sharma KG, Jalal AS (2013).Macro-block mode decision in MPEG-2 video compression using machine learning. Lecture Notes in Electrical Engineering. pp. 149–158
Liu J, Qiao F, Wei Q, Yang H (2013) A novel video compression method based on underdetermined blind source separation. Multimedia and Ubiquitous Engineering, Lecture Notes in Electrical Engineering 240:13–20
Masiero R, Quer G, Rossi M, Zorzi M (2009). A Bayesian analysis of compressive sensing data recovery in wireless sensor networks. In Proceedings of international conference on ultra-modern telecommunications & workshops (pp. 1–6). October 12–14, 2009
Mukherjee R, Debattista K, Bashford-Rogers T, Vangorp P, Mantiuk R, Bessa M, Waterfield B, Chalmers A (2016) Objective and subjective evaluation of high dynamic range video compression. Signal Process Image Commun 47:426–437
Needell D, Tropp JA (2009) CoSaMP: iterative signal recovery from incomplete and inaccurate sample. Journal of Applied and Computational Analysis 26(3):301–321
Patel VM, Chellappa R (2013) Sparse representation and compressive sensing for imaging and vision. Springer, Berlin
Paul M, Lin W, Lau CT, Lee BS (2013) Video coding with dynamic background, EURASIP. Journal on Advances in Signal Processing 11:1–17
Rajalakshmi K, Mahesh K (2016) A review on video compression and embedding techniques. International Journal of Computer Applications (0975–8887) 141(12):32–36
Tony CT, Wang L (2011) Orthogonal matching pursuit for sparse signal recovery with noise. IEEE Trans Inf Theory 57(7):4680–4688
Worasucheep C (2015) A Hybrid Artificial Bee Colony with Differential Evolution, International Journal of Machine Learning and Computing. 5
Xu D, Wang R (2016) Two-dimensional reversible data hiding-based approach for intra-frame error concealment in H.264/AVC. Signal processing: image communication. Vol 47:289–302
Yang J, Li WT, Shi XW, Xin L, Yu JF (2013) A hybrid ABC-DE algorithm and its application for time-modulated arrays pattern synthesis. IEEE Trans Antennas Propag 61(11):5485–5495. https://doi.org/10.1109/TAP.2013.2279093
Zatt B, Porto M, Scharcanski J (2010). Gop structure adaptive to the video content for efficient H.264/AVC encoding. Proceedings of 17th International conference in image processing. pp. 3053–3056
Zhi-xue L, Gang L, Hao Z, Xi-qin W (2012). Sparse-driven SAR imaging using MMV-StOMP. In Proceedings of 1st international workshop on compressed sensing applied to radar. IEEE Press, May 14–16
Author information
Authors and Affiliations
Corresponding author
Additional information
This article has been retracted. Please see the retraction notice for more detail: https://doi.org/10.1007/s11042-022-13971-0
About this article
Cite this article
Karthik Ganesh, R., Kanthavel, R. & Dhaya, R. RETRACTED ARTICLE: Development of video compression using EWNS linear transformation and un-repetition simulated contrary based resurgence procedure. Multimed Tools Appl 79, 3519–3541 (2020). https://doi.org/10.1007/s11042-018-6008-3
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11042-018-6008-3