ENHANCED AMBTC COMPRESSION TECHNIQUES FOR COLOR IMAGES

International Journal of Computer Science (IJCS) Published by SK Research Group of Companies (SKRGC)

Abstract

Image Compression methods have become inevitable now-a-days as the cost associated with storage and transmission of images is increasing in multi fold. Image Compression techniques are classified into two categories namely Lossy and Lossless techniques. Lossless techniques compress images without much loss of data and compressed images are the exact replica of the input images, whereas the reconstructed images of Lossy techniques are the approximation of input images. AMBTC is one of the Lossy techniques used for compressing images and it is very simple to implement and efficient in performance. In this paper, we have proposed an enhanced AMBTC color image compression technique. In this proposed method, multilevel compressionis achieved using the variants of AMBTC such as Bitmap Omission, Improved AMBTC, Interpolation and Quantization Subtraction and the performance is improved both in terms of quality of the reconstructed image and reduced storage cost. Color images are taken for the study. Simulated results show that the proposed method produces better visual quality and compression rate than that of the existing techniques.

References

1. PasiFranti, Olli Nevalainen and TimoKaukoranta, “Compression of digital Images by Block Truncation Coding:A Survey”, The Computer Journal, Vol.37, No.4, pp. 308-332, 1994.
2. S.Vimala, P.Uma, and S.Saranya, “Adaptive AMBTC using Bit Plane Patterns for Compressing Still Images”,International Journal of Computer Sciences and Engineering (IJCSE), Vol.6, Special Issue-4, pp. 81-85, May 2018.
3. Bibhas Chandra Dhara and BhabatoshChanda, “Block Truncation Coding using Pattern fitting”, Pattern Recognition, Vol.37, pp. 2131-2139, 2004.
4. S.Vimala, P.Uma Edwin and P.Anne Raja Reega Ruth, “Block Truncation Coding using Enhanced Interpolations and Lookup Procedures for Image Compression”, International Journal of Computer Applications (0975-8887), Vol.29, No.1, Sep 2011.
5. K.Somasundaram, S.Vimala, and P.Uma, “Extended Bit plane for Compressing Images using Absolute Moment Block Truncation Coding with Interpolations”, Proceedings in the National Conference on Signal and Image Processing (NCSIP), pp.73-75, 2012.
6. Yu-Chen Hu, “Predictive Grayscale Image Coding Scheme using VQ and BTC”, FundamentaInformaticae, Vol.78, pp. 239-255, 2007.
7. J.Mathews, M.S.Nair, and L.Jo, “A Novel Color Image Coding Technique using Improved BTC with k-means Quad Clustering”, Advances in Signal Processing and Intelligent Recognition Systems, Vol.264, pp. 347-357, 2014.
8. Yu-Chen Hu, “Predictive Moment preserving block truncation coding for gray-level image compression”, Journal of Electronic Imaging, Vol.13, No.4, pp.871-877, October 2004.
9. Wu-Lin Chen, Yu-Chen Hu, Kuo-Yu Liu, Chun-Chi Lo and Chia-Hsien Wen, “Variable-Rate Quadtree-segmented Block Truncation Coding for Color Image Compression”, International Journal of Signal Processing, Image Processing and Pattern Recognition, Vol.7, No.1, pp.65-76, 2014.
10. Abdel-QuahabBoudraa, AzeddineBeghdadi, Sidi Mohammed RedaDehak and RazvanLordache, “Fuzzy block truncation coding”, Optical Engineering, Vol.41, No.12, pp.3161-3167, Dec 2002.
11. Zhaoyang Xiang, Yu-Chen Hu, Heng Yao and Chuan Qin, “Adaptive and dynamic multi-grouping scheme for absolute moment block truncation coding”, Multimedia Tools and Applications, Vol.78, pp.7895-7909, 2019.
12. T.M.Amarunnishad, V.K.Govindan and Abraham T.Mathew, “Improving BTC image compression using a fuzzy complement edge operator”, Signal Processing, Vol.88, pp.2989-2997, 2008.
13. M.S.Meharban and S.Priya, “A Review on Image Compression using Halftoning Based BTC”, International Journal of Computational Science and Information Technology (IJCSIT), Vol.4, No.2, May 2016.
14. Kang-Sun Choi, “Bit plane modification for improving MSE-near optimal DPCM-based block truncation coding”, Digital Signal Processing, Vol.23, pp.1171-1180, 2013.
15. M.D.Lema and O.R.Mitchell, “Absolute Moment Block Truncation Coding and its applications to color image”, IEEE Transactions on communications, Vol.32, pp.1148-1157, 1984.
16. Y.Wu and D.C.Coll, “Single Bitmap Block Truncation coding of Color images”, IEEE Journal on Selected Areas in Communication, Vol.10,No.5, pp.952-959, Jun 1992.
17. Chen-Kuei Yang, Ja-Chen Lin and Wen-Hsiang Tsai, “Color image Compression by Moment Preserving and Block Truncation coding Techniques”, IEEE Transactions on Communications, Vol.45, No.12, pp.1513-1516, Dec 1997.
18. C.C Chang, T.S.Chen and L.Z.Chung, “A Colour image compression scheme based on two-layer absolute moment block truncation coding”, The Imaging Science Journal, Vol.48, No.2, pp.53-62, 2000.
19. Bibhas Chandra Dhara and BhabatoshChanda, “Color image compression based on block truncation coding using Pattern fitting”, Pattern Recognition, 2007.
20. Y.C Hu, B.H Su and P.Y Tsai, “Colour image coding scheme using absolute moment Block truncation coding and block prediction technique”, Imaging Science Journal, Vol.56, N0.5, pp.254-270, 2008.
21. Y.C Hu, C.Y Li, J.C Chuang and C.C LO, “Variable-Rate Color Image Quantization based Quadtree Segmentation”, Opto-Electronics Review, Vol.19, No.3, pp.282-289, 2011.
22. Yu-Chen Hu, I-Cheng Chang, Kuo-Yu Liu and Che-Lun Hung, “Improved color image coding scheme based on single bitmap block truncation coding”, Optical Engineering, Vol.53, No.9, Sep 2014.
23. Zhihong Li, Qiang Jin, Chin-Chen Chang, Li Liu and Anhong Wang, “A Common Bitmap Block Truncation Coding for color images based on Binary Ant Colony Optimization”, KSII Transactions on Internet and Information Systems, Vol.10, No.5, pp.2326-2345, May 2016.
24. Lige Zhang, Xiaolin Qin, Qing Li, HaoyuePeng and Yu Hou, “Single bitmap block truncation coding of color images usinf Hill Climbing Algorithm”, Computer Vision and Pattern Recognition, Jul 2018.
25. Rajeev Kumar, Samayveer Singh and Ki-Hyun Jung, “Human Visual System based Enhanced AMBTC for Color Image Compression using Interpolation”,2019 6th International Conference on Signal Processing and Integrated Networks (SPIN), Noida, India, pp. 903-907, 2019.
26. M. Sathish Kumar and B. Indrani, "Brain Storm Optimization based Association Rule Mining Model for Intelligent Phishing URLs Websites Detection," 2020 Fourth International Conference on Computing Methodologies and Communication (ICCMC), 2020, pp. 640-646, doi: 10.1109/ICCMC48092.2020.ICCMC-000119.

Keywords

AMBTC, Bitrate, Interpolation, Quantization Subtraction, PSNR.