Pixel Based Techniques for Gray Image Compression: A review
DOI:
https://doi.org/10.29304/jqcm.2022.14.2.967Keywords:
DPCM and pixel-based techniques, image compression, lossless/lossyAbstract
Currently, with the huge increase in modern communication and network applications, the speed of transformation and storing data in compact forms are pressing issues. Daily an enormous amount of images are stored and shared among people every moment, especially in the social media realm, but unfortunately, even with these marvelous applications, the limited size of sent data is still the main restriction's, where essentially all these applications utilized the well-known Joint Photographic Experts Group (JPEG) standard techniques, in the same way, the need for construction of universally accepted standard compression systems urgently required to play a key role in the immense revolution.
This review is concerned with Differential pulse code modulation (DPCM) and pixel-based techniques, where the spatial domain is exploited to compress images efficiently in terms of compression performance and preserving quality. The new pixel-based method overcomes predictive coding constraints with fewer residues and higher compression ratios.
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References
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[2] G. Al-Khafaji and S. Fadhil, “Image Compression based on Fixed Predictor Multiresolution Thresholding of Linear Polynomial Nearlossless Techniques,” J. Al-Qadisiyah Comput. Sci. Math.,vol.9, pp. 35–44, 2017
[3] Khalid Sayood, Introduction To Data Compression, vol. 254. 2000.
[4] R. C. Gonzalez and R. E. Woods. Digital Image Processing, 4TH EDITION, Pearson, 2018.
[5] G. K. T. Al-khafaji, Intra and inter frame compression for video streaming,Ph.D .Sci.thesis, University of Exeter , England ,(2012).
[6 A. Abd-Alhussain. ,Photo Passport Compression using Hybrid Techniques, M.Sci.thesis , Baghdad University ,Iraq,( 2021)
[7] Abdullah A. Hussain, G. AL-Khafaji “A Pixel Based Method for Image Compression” Tikrit J. Pure Sci., vol.26,pp. 1813–1662 , 2021.
[8] H. Al-Mahmood and Z. Al-Rubaye, “Lossless Image Compression based on Predictive Coding and Bit Plane Slicing,” Int. J. Comput. Appl., vol. 93, no. 1, pp. 1–6, 2014.
[9] A. C. Antony and C. Thomas, “A Lossless Image Compression Based On Hierarchical Prediction and Context Adaptive Coding,” International Journal of Engineering Research and General Science, Vol.3,pp. 517–521, 2015.
[10] P. Suresh Babu and S. Sathappan, “Efficient lossless image compression using modified hierarchical forecast and context adaptive system,” Indian J. Sci. Technol., vol.8, 2015.
[11] M. Abo-Zahhad, R. R. Gharieb, S. M. Ahmed, and M. K. Abd-Ellah, “Huffman Image Compression Incorporating DPCM and DWT,” J. Signal Inf. Process. , pp. 123–135, 2015.
[12] R. R. S. Tomar and K. Jain, “Lossless Image Compression Using Differential Pulse Code Modulation and its Application,”. International Journal of Signal Processing, Image Processing and Pattern Recognition. vol.8, pp. 397–400, 2016.
[13] A. T.Hashim and S.A. Ali, “Color Image Compression Using DPCM with DCT, DWT and Quadtree Coding Scheme,” Eng. &Tech.Journal, vol.34, pp. 585–597, 2016.
[14] C. Narmatha and P. Manimegalai, “A LS-Compression Scheme for Grayscale Images Using Pixel Based Technique,”, IEEE International Conference on Innovations in Green Energy and Healthcare Technologies(ICIGEHT’17) , 2017.
[15] M. V Gashnikov, “DPCM with an adaptive extrapolator for image compression,” 3rd International conference “Information Technology and Nanotechnology 2017”pp. 72–77.
[16] R. Tyagi, R. Yadav, and S. Sharma, “Image Compression Using DPCM with LMS Algorithm,” Int. Res. J. Eng. Technol., vol. 4, no. 1, pp. 490–493, 2017.
[17] M. Uvaze, A. Ayoobkhan, E. Chikkannan, and K. Ramakrishnan, “Lossy image compression based on prediction error and vector quantisation,”EURASIP Journal on Image and Video Processing, 2017.
[18] M. A. Kabir and M. R. H. Mondal, “Edge-based and prediction- based transformations for lossless image compression,” J. Imaging, vol. 4, 2018.
[19] A. Maksimov and M. Gashnikov, “Parameterized four direction contour-invariant extrapolator for DPCM image compression,” in Tenth International Conference on Digital Image Processing (ICDIP 2018), (2018), p. 143.
[20] A. Shankar and A. Kannammal, “Multiscale Approach For Region Based Medical Image Compression,” International Journal of Emerging Technology and Advanced Engineering,vol.8,pp.12-17, 2018.
[21] N. A. N. Azman, S. Ali, R. A. Rashid, F. A. Saparudin, and M. A. Sarijari, “A hybrid predictive technique for lossless image compression,” Bull. Electr,vol.8, pp. 1289–1296, 2019.
[22] E. L. L. Cabral, G. Sabundjian, and N. Conti, “Pixel-Position-Based Lossless Image Compression Algorithm,” , International Journal of Innovative Studies in Sciences and Engineering Technology (IJISSET) ,vol.5,pp.21-29, 2019.
[23] G. Al-Khafaji and H. H. Khalaf, “Hierarchical Fixed Prediction of Mixed based for Medical Image Compression,” International Journal of Computer Science and Mobile Computing,vol. 9, pp. 124–130, Feb.2020.
[24] M. Education, V. L. Praba, and R. S. Rajesh, “Image Compression Based On Octagon Based Intra Prediction,” vol. 12, no. 3, pp. 6144–6151, 2021.
[25] Rhee, Y. Il Jang, S. Kim, and N. I. Cho, “Lossless Image Compression by Joint Prediction of Pixel and Context Using Duplex Neural Networks,” IEEE Access, vol. 9, pp. 86632-86645, 2021.
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Published
2022-07-06
How to Cite
Abeda, Z. H., & AL-Khafaji, G. K. (2022). Pixel Based Techniques for Gray Image Compression: A review. Journal of Al-Qadisiyah for Computer Science and Mathematics, 14(2), Comp Page 59–70. https://doi.org/10.29304/jqcm.2022.14.2.967
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Computer Articles
