Improved block based segmentation algorithm for compression of compound images
Pages 3213 - 3225
Abstract
Compression and transmission of compound images are essential processes in real time applications where there is a necessity that the compression technique should attain high compression ratio, low complexity, high PSNR value and a required level of security. This paper proposes a novel method for block-based compound image compression. The pictorial blocks and text/graphics blocks are separated from the compound image. The pictorial blocks are compressed using discrete Haar wavelet transformation and text/graphics colors are mapped to primary colors using color quantization algorithm and the resulting index values are then compressed using the lossless Huffman coding technique. The compressed image is then encrypted using an Advanced Encryption Standard algorithm which ensures that the transmission is fast and highly secured. Experimental results conclude that the proposed algorithm provides better results like low complexity, high compression ratio and a high PSNR value than most of the other image compression techniques.
References
[1]
D. Maheswari and V. Radha, Comparison of layer and block based classification in compound image compression, International Journal of Computer Science and Information Technologies 2(2) (2011), 888-890.
[2]
D. Maheswari and V. Radha, Enhanced hybrid compound image compression algorithm combining block and layer-based segmentation, The International Journal of Multimedia Its Applications (IJMA) 3(4) (2011), 946-957.
[3]
C. Lan, G. Shi and F. Wu, Compress compound images in H.264/MPGE-4 AVC by exploiting spatial correlation, IEEE Transactions on Image Processing 19(4) (2010).
[4]
H. Cheng, G. Feng and A. Charles, Bouman, Rate-Distortion Based Segmentation for MRC Compression, Proc PIE, Vol. 4663, 2002, pp. 86-97.
[5]
W. Ding, D. Liu, Y. He and F. Wu, Block-based Fast Compression for Compound Images, IEEE International Conference on Multimedia and Expo, 2006, pp. 809-812.
[6]
H.D. Felzenszwalb and P.W. Rucklidge, DigiPaper: A versatile color document image representation, Proc ICIP, Vol. I, 1999, pp. 219-223.
[7]
L.H. Sharpe and R. Buckley, JPEG 2000. jpm file format: A layered imaging architecture for document imaging and basic animation on the web, Proceedings of SPIE, Vol. 4115, 2000, pp. 464-475.
[8]
A. Said and A. Drukarev, Simplified segmentation for compound image compression, Proceeding of ICIP' 1999, 1999, pp. 229-233.
[9]
L. Bottou, P. Haffner, P. Howard, P. Simard, Y. Bengio and Y. LeCun, High quality document image compression using DjVu, Journal of Electronic Imaging 7(3) (1998), 410-425.
[10]
K.H. Talukder and K. Harada, Discrete Wavelet Transform for Image Compression and A Model of Parallel Image Compression scheme for Formal Verification, Proceedings of the World Congress on Engineering, 1, 2007.
[11]
Lin and T. Pengwei Hao, Compound image compression for real-time computer screen image transmission, IEEE Transactions on Image Processing 14(8) (2005), 993-1005.
[12]
W. Ding, Y. Lu and F. Wu, Enable efficient compound image compression in H.264/AVC intra coding, IEEE International Conference on Image Processing 2 (2007), 337-340.
[13]
J. Daemen and V. Rijmen, The Block Cipher Rijndael, Proceeding CARDIS '98 Proceedings of the the International Conference on Smart Card Research and Applications, 2000, pp. 277-284.
[14]
H. Jagadhish and L.M. Kadlaskar, A new lossless method of image compression and decompression using huffman coding techniques, Journal of Theoretical and Applied Information Technology (2010), 18-23.
[15]
T. Lin, P. Hao and S. Uk Lee, Efficient coding of computer generated compound images, IEEE International Conference on Image Processing 1 (2005), 561-564.
[16]
X. Li and S. Lei, Block-based segmentation and adaptive coding for visually lossless compression of scanned documents, ICIP 3 (2001), 450-453.
[17]
S. Mohankrishna, S. Sri Hari, T.V. Trinadh and G. RajaKumar, A novel approach for reduction of huffman cost table in image compression, International Journal of Computer Applications 20(6) (2011), 33-38.
[18]
Md. Mosaddik Hasan, Md. Sohel Parvez, J. Islam and S. Datta, A novel approach to remove salt-and-pepper noise on a compound image using a non-liner filter, IJECT 2(1) (2011), 153-155.
[19]
S. Gai, G. Yang and S. Zhang, Multiscale texture classification using reduced quaternion wavelet transform [J], International Journal of Electronics and Communications 67(3) (2013), 233-241.
[20]
S. Gai, G. Yang and W. Minghua, Employing quaternion wavelet transform for banknote classification [J], Neurocompuing 118(8) (2013), 171-178.
- Improved block based segmentation algorithm for compression of compound images
Recommendations
Compound image compression for real-time computer screen image transmission
We present a compound image compression algorithm for real-time applications of computer screen image transmission. It is called shape primitive extraction and coding (SPEC). Real-time image transmission requires that the compression algorithm should ...
Simplified DCT based segmentation with efficient coding of computer screen images
ICIMCS '09: Proceedings of the First International Conference on Internet Multimedia Computing and ServiceThis paper presents a novel single pass block classification algorithm for efficient coding of computer screen images which consists of multimedia elements like text, graphics and natural images. The objective is to minimize the loss of visual quality ...
Compress compound images in H.264/MPGE-4 AVC by exploiting spatial correlation
Compound images are a combination of text, graphics and natural image. They present strong anisotropic features, especially on the text and graphics parts. These anisotropic features often render conventional compression inefficient. Thus, this paper ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
Publisher
IOS Press
Netherlands
Publication History
Published: 01 November 2014
Author Tags
Qualifiers
- Article
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 0Total Downloads
- Downloads (Last 12 months)0
- Downloads (Last 6 weeks)0
Reflects downloads up to 11 Jan 2025