A hybrid predictive technique for lossless image compression
Compression of images is of great interest in applications where efficiency with respect to data storage or transmission bandwidth is sought.The rapid growth of social media and digital networks have given rise to huge amount of image data being accessed and exchanged daily. However, the larger the...
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| Format: | Article |
| Language: | English |
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Institute of Advanced Engineering and Science
2019
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| Online Access: | http://eprints.utm.my/91806/1/SamuraAli2019_A%20HybridPredictiveTechnique.pdf |
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| author | Azman, N. A. N. Ali, S. Rashid, R. A. Saparudin, F. A. Sarijari, M. A. |
| author_facet | Azman, N. A. N. Ali, S. Rashid, R. A. Saparudin, F. A. Sarijari, M. A. |
| author_sort | Azman, N. A. N. |
| collection | ePrints |
| description | Compression of images is of great interest in applications where efficiency with respect to data storage or transmission bandwidth is sought.The rapid growth of social media and digital networks have given rise to huge amount of image data being accessed and exchanged daily. However, the larger the image size, the longer it takes to transmit and archive. In other words, high quality images require huge amount of transmission bandwidth and storage space. Suitable image compression can help in reducing the image size and improving transmission speed. Lossless image compression is especially crucial in fields such as remote sensing healthcare network, security and military applications as the quality of images needs to be maintained to avoid any errors during analysis or diagnosis. In this paper, a hybrid prediction lossless image compression algorithm is proposed to address these issues. The algorithm is achieved by combining predictive Differential Pulse Code Modulation (DPCM) and Integer Wavelet Transform (IWT). Entropy and compression ratio calculation are used to analyze the performance of the designed coding. The analysis shows that the best hybrid predictive algorithm is the sequence of DPCM-IWT-Huffman which has bits sizes reduced by 36%, 48%, 34% and 13% for tested images of Lena, Cameraman, Pepper and Baboon, respectively. © 2019 Institute of Advanced Engineering and Science. |
| first_indexed | 2024-03-05T20:54:53Z |
| format | Article |
| id | utm.eprints-91806 |
| institution | Universiti Teknologi Malaysia - ePrints |
| language | English |
| last_indexed | 2024-03-05T20:54:53Z |
| publishDate | 2019 |
| publisher | Institute of Advanced Engineering and Science |
| record_format | dspace |
| spelling | utm.eprints-918062021-07-28T08:47:41Z http://eprints.utm.my/91806/ A hybrid predictive technique for lossless image compression Azman, N. A. N. Ali, S. Rashid, R. A. Saparudin, F. A. Sarijari, M. A. TK Electrical engineering. Electronics Nuclear engineering Compression of images is of great interest in applications where efficiency with respect to data storage or transmission bandwidth is sought.The rapid growth of social media and digital networks have given rise to huge amount of image data being accessed and exchanged daily. However, the larger the image size, the longer it takes to transmit and archive. In other words, high quality images require huge amount of transmission bandwidth and storage space. Suitable image compression can help in reducing the image size and improving transmission speed. Lossless image compression is especially crucial in fields such as remote sensing healthcare network, security and military applications as the quality of images needs to be maintained to avoid any errors during analysis or diagnosis. In this paper, a hybrid prediction lossless image compression algorithm is proposed to address these issues. The algorithm is achieved by combining predictive Differential Pulse Code Modulation (DPCM) and Integer Wavelet Transform (IWT). Entropy and compression ratio calculation are used to analyze the performance of the designed coding. The analysis shows that the best hybrid predictive algorithm is the sequence of DPCM-IWT-Huffman which has bits sizes reduced by 36%, 48%, 34% and 13% for tested images of Lena, Cameraman, Pepper and Baboon, respectively. © 2019 Institute of Advanced Engineering and Science. Institute of Advanced Engineering and Science 2019 Article PeerReviewed application/pdf en http://eprints.utm.my/91806/1/SamuraAli2019_A%20HybridPredictiveTechnique.pdf Azman, N. A. N. and Ali, S. and Rashid, R. A. and Saparudin, F. A. and Sarijari, M. A. (2019) A hybrid predictive technique for lossless image compression. Bulletin of Electrical Engineering and Informatics, 8 (4). pp. 1289-1296. ISSN 2089-3191 http://www.dx.doi.org/10.11591/eei.v8i4.1612 DOI: 10.11591/eei.v8i4.1612 |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering Azman, N. A. N. Ali, S. Rashid, R. A. Saparudin, F. A. Sarijari, M. A. A hybrid predictive technique for lossless image compression |
| title | A hybrid predictive technique for lossless image compression |
| title_full | A hybrid predictive technique for lossless image compression |
| title_fullStr | A hybrid predictive technique for lossless image compression |
| title_full_unstemmed | A hybrid predictive technique for lossless image compression |
| title_short | A hybrid predictive technique for lossless image compression |
| title_sort | hybrid predictive technique for lossless image compression |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| url | http://eprints.utm.my/91806/1/SamuraAli2019_A%20HybridPredictiveTechnique.pdf |
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