
Proceedings Paper
Method for low-light-level image compression based on wavelet transformFormat | Member Price | Non-Member Price |
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Paper Abstract
Low light level (LLL) image communication has received more and more attentions in the night vision field along with the advance of the importance of image communication. LLL image compression technique is the key of LLL image wireless transmission. LLL image, which is different from the common visible light image, has its special characteristics. As still image compression, we propose in this paper a wavelet-based image compression algorithm suitable for LLL image. Because the information in the LLL image is significant, near lossless data compression is required. The LLL image is compressed based on improved EZW (Embedded Zerotree Wavelet) algorithm. We encode the lowest frequency subband data using DPCM (Differential Pulse Code Modulation). All the information in the lowest frequency is kept. Considering the HVS (Human Visual System) characteristics and the LLL image characteristics, we detect the edge contour in the high frequency subband image first using templet and then encode the high frequency subband data using EZW algorithm. And two guiding matrix is set to avoid redundant scanning and replicate encoding of significant wavelet coefficients in the above coding. The experiment results show that the decoded image quality is good and the encoding time is shorter than that of the original EZW algorithm.
Paper Details
Date Published: 18 October 2001
PDF: 7 pages
Proc. SPIE 4586, Wireless and Mobile Communications, (18 October 2001); doi: 10.1117/12.445262
Published in SPIE Proceedings Vol. 4586:
Wireless and Mobile Communications
Hequan Wu; Jari Vaario, Editor(s)
PDF: 7 pages
Proc. SPIE 4586, Wireless and Mobile Communications, (18 October 2001); doi: 10.1117/12.445262
Show Author Affiliations
Shaoyuan Sun, Nanjing Univ. of Science and Technology (China)
Baomin Zhang, Nanjing Univ. of Science and Technology (China)
Baomin Zhang, Nanjing Univ. of Science and Technology (China)
Liping Wang, Nanjing Univ. of Science and Technology (China)
Lianfa Bai, Nanjing Univ. of Science and Technology (China)
Lianfa Bai, Nanjing Univ. of Science and Technology (China)
Published in SPIE Proceedings Vol. 4586:
Wireless and Mobile Communications
Hequan Wu; Jari Vaario, Editor(s)
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