A Survey: Restoration of Compressed Image

  • Authors

    • M. S Sujithra NI University
    • N. SugithaSugitha
    2019-03-12
    https://doi.org/10.14419/ijet.v7i4.23201
  • Blocking Artifacts, Deblocking Method, Maximum of a Posteriori, Projection onto Convex Sets, Sparse Dictionary Learning.
  • Abstract

    In recent years, blocking artifacts are the one of the major problem faced by the image compression due to quantization bit constraints or inter-block correlation in decompression. The various methods used to remove the blocking artifacts are broadly classified as deblocking methods and estimation / learning based methods. Both the methods are further classified into filtering approach and restoration of transform coefficients, maximum of a posteriori, projection onto convex sets and sparse dictionary learning. All these image restoration techniques are applied to restore the compressed image by considering the compressed image as degraded image. This paper presents various techniques for restoring compressed image and thereby maintaining the perceptual quality of the image.

     

     

     
  • References

    1. [1] Banham, M R and Katsaggelos,A K, â€Digital image restorationâ€, IEEE Transaction on Signal Processing, Vol. 14 No.2, (1997), pp. 24 - 41. https://doi.org/10.1109/79.581363.

      [2] Lee,J S, “Digital image smoothing and the sigma filterâ€, Computer Vision and Graph in Image Processing, Vol. 24, (1983), pp. 255 – 269. https://doi.org/10.1016/0734-189X(83)90047-6.

      [3] George, A T. Dimitrios Tzovaras and Michael Gerassimos, “Blocking Artifacts detection and reduction in Compressed dataâ€, IEEE Transactions on Circuits and Systems for video Technology, Vol. 12 No.10, (2002), pp.877 - 890. https://doi.org/10.1109/TCSVT.2002.804880.

      [4] Hsu,Y F and Chen,Y C, “A new adaptive median filter for removing blocking effectsâ€, IEEE Transactions Consumer Electronics, Vol. 39 No.3, (1993) , pp.510 - 513. https://doi.org/10.1109/30.234628.

      [5] Reeve, H C and Lim, J S, “Reduction of blocking artifacts in image codingâ€, Optical Engineering, Vol. 23 No.1, (1984), pp.34 - 37.

      [6] Jarske,T. Haavisto, P. and Defe’e,I, “Post-filtering methods for reducing blocking effects from coded imagesâ€, IEEE Transactions Consumer Electronics, Vol. 40 No.3, (1994), pp.521 - 526. https://doi.org/10.1109/30.320837.

      [7] Kuo,C J. and Hseih,R J, “Adaptive post processor for block encoded imagesâ€, IEEE Transactions on Circuits and Systems for Video Technology, Vol. 5 No.4, (1995), pp.298 - 304. https://doi.org/10.1109/76.465083.

      [8] Meier,T. Ngan,K N and Crebbin,G, “A region based algorithm for enhancement of images degraded by blocking effectsâ€, Proceedings of the IEEE TENCON Digital Signal Processing Applications, Australia, (1996), pp.405 - 408. https://doi.org/10.1109/TENCON.1996.608849.

      [9] Lee,Y L. Kim,H C and Park,H W,â€Blocking effect reduction by JPEG images by Signal Adaptive filteringâ€, IEEE Transactions on Image Processing, Vol. 7 No.2 , .(1998), pp.229 - 234. https://doi.org/10.1109/83.661000.

      [10] Buyue Zhang. Jan P Allebach, “Adaptive Bilateral Filter for Sharpness Enhancement and Noise Removalâ€, IEEE Transactions on Image Processing, Vol. 17 No.17, (2008), pp. 664 – 678. https://doi.org/10.1109/TIP.2008.919949.

      [11] Nath,N K. Hazarika,D. and Mahanta,A, “Blocking Artifacts reduction using adaptive bilateral filteringâ€, Proceedings of the IEEE International conference on Signal Processing and Communication, (2010), pp. 1-5.

      [12] Dung T Vo. Truong Q Nyuyen. Sehoon Yea and Vetro,A. “Adaptive Fuzzy Filtering for Artifact Reduction in Compressed Images and Videosâ€, IEEE Transactions on Image Processing, Vol. 18 No.6, (2009), pp. 1166 – 1178. https://doi.org/10.1109/TIP.2009.2017341.

      [13] Wang,C. Zhou, J and Liu,S, “Adaptive non-local means filter for image deblockingâ€, Signal Processing: Image Communication, Vol. 28, (2013), pp. 522 - 530. https://doi.org/10.1016/j.image.2013.01.006.

      [14] Tao Chen. Hong Ren Wu and Bin Qiu, “Adaptive post filtering of Transform Coefficients for the reduction of blocking artifactsâ€, IEEE Transaction on Circuits Systems and Video Technology, Vol. 11 No.5,(2001), pp. 594 – 602. https://doi.org/10.1109/76.920189.

      [15] Luo, Y and Ward,R K, “Removing the blocking artifacts of block based DCT compressed imagesâ€, IEEE Transaction on Image Processing, Vol. 12 No.7, (2003), pp. 838 – 842. https://doi.org/10.1109/TIP.2003.814252.

      [16] Popovici,I and Douglas,W, “Locating edges and removing ringing artifacts in JPEG images by frequency-domain analysisâ€, IEEE Transactions on Image Processing, Vol. 16 No.5, (2007) , pp. 1470 – 1474. https://doi.org/10.1109/TIP.2007.891782.

      [17] Kim,S D. Kim,H M and Ra,J B, “A deblocking filter with two separate modes in block based video codingâ€, IEEE Transactions on Circuits and Systems for Video Technology, Vol. 9 No.1, (1999), pp.156 -160. https://doi.org/10.1109/76.744282.

      [18] Joch,L.P. Lainema,A. Bjntegaard,J and Karczewicz,G, “Adaptive deblocking filterâ€, IEEE Transactions on Circuits and Systems for Video Technology, Vol. 13 No.7, (2003), pp. 614 – 619.

      [19] Tai,S C. Chen,Y Y and Sheu,S F, “Deblocking filter for low bit rate MPEG4 videoâ€, IEEE transactions on circuits and systems for video technology, Vol. 15 No.6, (2005), pp.731 – 733.

      [20] Averbuch,A Z. Schclar,A and Donoho,D L, “Deblocking of block- transform compressed images using weighted sums of symmetrically aligned pixelsâ€, IEEE Transactions on Image Processing, Vol.14 No.2,(2005),pp.200– 212. https://doi.org/10.1109/TIP.2004.840688.

      [21] Taehwan Lim. Jiman Ryu and Jongho Kim,†Adaptive deblocking method using a transform table of different dimension DCTâ€, IEEE Transactions on Consumer Electronics, Vol. 54 No.4, (2008), pp. 1 - 5. https://doi.org/10.1109/TCE.2008.4711263.

      [22] Ramakrishna Palaparthi and Vinay Kumar Srivastava. “A simple deblocking method for the reduction of blocking artifactsâ€, IEEE Students Conference on Electrical, Electronics and Computer Science, (2012), pp.1 – 4. https://doi.org/10.1109/SCEECS.2012.6184788.

      [23] Minami,S and Zakhor,A, “An optimization approach for removing blocking effects in transform codingâ€, IEEE Transactions on Circuits and Systems for Video Technology, Vol. 5 No.2, (1995), pp.74 – 85. https://doi.org/10.1109/76.388056.

      [24] Jeon,B and Jeong,J, “Blocking artifacts reduction in image compression with block boundary discontinuity criterionâ€, IEEE Transaction on Circuits Systems and Video Technology, Vol. 8 No.3, (1998), pp.345 –357. https://doi.org/10.1109/76.678634.

      [25] Zeng,B, “Reduction of blocking effect in DCT-coded images using zero-masking techniques†, Signal Processing, Vol. 79 No.2, (1999), pp.205 – 211. https://doi.org/10.1016/S0165-1684(99)00094-8.

      [26] Shizhong Liu and Bovil,A C, “Efficient DCT-domain blind measurement and Reduction of blocking Artifactsâ€, IEEE Transaction on Circuits Systems and Video Technology, Vol. 12 No.12, (2002), pp. 1139 – 1149. https://doi.org/10.1109/TCSVT.2002.806819.

      [27] Liew,A W C and Yan,H, “Blocking artifacts suppression in block-coded images using overcomplete wavelet representationâ€, IEEE Transactions on Circuits and Systems for Video Technology, Vol. 14 No.4, (2004),pp. 450-461.
      https://doi.org/10.1109/TCSVT.2004.825555.

      [28] Figueiredo,M A T and Nowak,R D, “An EM algorithm for wavelet-based image restorationâ€, IEEE Transactions on Image Processing, Vol. 12 No.8, (2003), pp. 906 – 916. https://doi.org/10.1109/TIP.2003.814255.

      [29] Rourke,T P O and Stevenson,R L, “Improved image decompression for reduced transform coding artifactsâ€, IEEE Transactions on Circuits and Systems for Video Technology, Vol. 5 No. 6, (1995), pp. 490 – 499. https://doi.org/10.1109/76.475891.

      [30] [30] Ozcelik. Taner, J C. Brailean and Katsaggelos A K, “Image and video compression algorithms based on recovery techniques using mean field annealingâ€, Proceedings of the IEEE , Vol. 83 No.2 , (1995), pp. 304 – 316. https://doi.org/10.1109/5.364460.

      [31] Meier,T. Ngan,K N and Crebbin,G, “Reduction of blocking artifacts in image and video codingâ€, IEEE Transactions on Circuits and Systems for Video Technology, Vol. 9 No.3, (1999), pp. 490 – 500. https://doi.org/10.1109/76.754778.

      [32] Xinfeng Zhang. RuiqinXiong. Xiaopeng Fan. Siwei Ma. Wen Gao, “Compression Artifact Reduction by Overlapped-Block Transform Coefficient Estimation With Block Similarityâ€, IEEE Transactions on Image Processing, Vol. 22 No.12, (2013), pp.4613 – 4626. https://doi.org/10.1109/TIP.2013.2274386.

      [33] Unal,G B and Cetin,A E, “Restoration of error-diffused images using projection onto convex setsâ€, IEEE Transactions on Image Processing, Vol. 10 No.12, (2001), pp.1836 – 1841. https://doi.org/10.1109/83.974568.

      [34] Zakhor,A, “Iterative procedures for reduction of blocking effects in transform image codingâ€, IEEE Transactions on Circuits and Systems for Video Technology, Vol. 2 No.1, (1992), pp. 91 – 95. https://doi.org/10.1109/76.134377.

      [35] Zou, J J and Yan,H, “A deblocking method for BDCT compressed images based on adaptive projectionsâ€, IEEE Transaction on Circuits and System for Video Technology, Vol. 15 No.3, (2005), pp. 430 – 435. https://doi.org/10.1109/TCSVT.2004.842610.

      [36] Yang,Y and Galatsanos,N P, “Removal of Compression Artifacts Using Projections onto Convex Sets and Line Process Modelingâ€, IEEE Transactions on Image Processing, Vol. 6, No.10, (1997), pp. 1345 -1357. https://doi.org/10.1109/83.624945.

      [37] Yoon Kim. Chun-Su Park. and Sung-Jea Ko, “Fast POCS based post-processing technique for HDTVâ€, IEEE Transaction in Consumer Electronics, Vol. 49 No.4,.(2003), pp.1438 – 1447. https://doi.org/10.1109/TCE.2003.1261252.

      [38] Paek,H. Kim,R C and Lee,S, “On the POCS-based postprocessing technique to reduce the blocking artifacts in transform coded imagesâ€, IEEE Transactions on Circuits and Systems for Video Technology, Vol. 8 No.3, (1998), pp. 358 – 367. https://doi.org/10.1109/76.678636.

      [39] Hoon Paek. Rin-Chul Kim and Sang-Uk Lee, “A DCT-based spatially adaptive post processing technique to reduce the blocking artifacts in transform coded imagesâ€, IEEE Transaction on Circuits and Systems in Video Technology, Vol. 10 No.1, (2000), pp.36 – 41. https://doi.org/10.1109/76.825856.

      [40] Ogawa,T. and Haseyama,H, “Missing intensity interpolation using a kernel PCA-based POCS algorithm and its applicationsâ€, IEEE Transactions on Image Processing, Vol. 20 No.2, (2011), pp.417 – 432. https://doi.org/10.1109/TIP.2010.2070072.

      [41] Zheng Zhang. Jian Yang and David Zhang, “A Survey of sparse representation: algorithms and applicationsâ€, IEEE Biometrics Compendium, Vol. 3 No.1, (2015), pp.490 – 530.

      [42] Hyvarinen, A, “Fast and robust fixed-point algorithms for independent component analysisâ€, IEEE Transactions on Neural Networks, Vol. 10 No.3, (1999), pp.626 – 634. https://doi.org/10.1109/72.761722.

      [43] Aharon. Michal. Michael Elad, and Alfred Bruckstein, “K-SVD: An algorithm for designing overcomplete dictionaries for sparse representationâ€, IEEE Transactions on Signal Processing, Vol. 54, No.11, (2006), pp. 4311- 4322. https://doi.org/10.1109/TSP.2006.881199.

      [44] Inchang Choi and Sunyeong Kim, “A learning based Approach to reduce JPEG Artifacts in Image Mattingâ€, Proceedings of the IEEE Conferences in Computer Vision, Sydney, NSW, Australia, (2013) ,pp. 2880 – 2887.

      [45] Liu,X. Wu,X. Zhou,J and Zhao,D, “Sparsity-based decoding of compressed images in Transform Domainâ€, Proceedings of the IEEE International Conference on Image Processing, Melbourne, VIC, Australia, (2013), pp. 563 – 566.

      [46] Chang Huibin. Michael,K and Zeng Tieyong, “Reducing Artifact in JPEG Decompression via a Learned Dictionaryâ€, IEEE Transactions on Image Processing, Vol.62 No.3, (2014) ,pp.718 – 728. https://doi.org/10.1109/TSP.2013.2290508.

      [47] Liu,X. Wu,X. Zhou,J and Zhao,D, “Inter-block consistent soft decoding of jpeg images with sparsity and graph-signal smoothness priorsâ€, Proceedings of the IEEE International Conference on Image Processing , Quebeu City, QC, Canada, (2015), pp.1628 – 1632.

      [48] Liu,X. Wu,X. Zhou,J and Zhao,D, “Data-Driven Soft Decoding of Compressed Images in Dual Transform-Pixel Domainâ€, IEEE Transactions on Image Processing, Vol. 25 No.4 , (2016) , pp.1649 - 1659. https://doi.org/10.1109/TIP.2016.2526910.

      [49] Parsa, Omidi, Mohsin Zafer, Moein Mozaffarzadeh, Ali Hariri†A novel dictionary –based image reconstruction for photo acoustic computed tomography, Journal of Applied Sciences, Vol. 8 No.9, (2018),pp. 1570 https://doi.org/10.3390/app8091570.

      [50] Saiprasad Ravishankar,Anish Lahiri, Cameron Blocker, Jeffery A Fessler, â€Deep Dictionary-transform Learning for image reconstructionâ€, IEEE International Symposium on Biomedical Imaging, Washington, DC,USA,(2018),pp.1208-1212.

      [51] Gorodnitsky,I F. and Rao,B D,â€Sparse signal reconstruction from limited data using FOCUSS: A re-weighted minimum norm algorithmâ€, IEEE Transaction on Signal Processing, Vol. 45 No.3, (1997), pp. 600-616. https://doi.org/10.1109/78.558475.

      [52] Zhang,Q and Li,B, “Discriminative k-svd for dictionary learning in face recognitionâ€, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , San Francisco, CA, USA, (2010), pp. 2691 – 2698.

      [53] Tropp,J A. and Gilbert,A C, “Signal recovery from random measurements via orthogonal matching pursuitâ€, IEEE Transactions on Information Theory, Vol. 53 No.12, (2007) , pp. 4655–4666. https://doi.org/10.1109/TIT.2007.909108.

      [54] Wright,J. Yang,A Y. Ganesh,A. Sastry,S S. and Ma,Y, “Robust face recognition via sparse representationâ€, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 31 No.2, (2009), pp. 210–227. https://doi.org/10.1109/TPAMI.2008.79.

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  • How to Cite

    S Sujithra, M., & SugithaSugitha, N. (2019). A Survey: Restoration of Compressed Image. International Journal of Engineering & Technology, 7(4), 5167-5173. https://doi.org/10.14419/ijet.v7i4.23201

    Received date: 2018-12-05

    Accepted date: 2019-02-04

    Published date: 2019-03-12