Computer Vision and Image Understanding - Special issue on underwater computer vision and pattern recognition
Wavelet Image and Video Compression
Wavelet Image and Video Compression
A Lossy Image Codec Based on Index Coding
DCC '96 Proceedings of the Conference on Data Compression
Embedded image coding using zerotrees of wavelet coefficients
IEEE Transactions on Signal Processing
IEEE Transactions on Image Processing
A new, fast, and efficient image codec based on set partitioning in hierarchical trees
IEEE Transactions on Circuits and Systems for Video Technology
A study on the SPIHT image coding technique for underwater acoustic communications
Proceedings of the Sixth ACM International Workshop on Underwater Networks
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Underwater image compression has been the key technology for transmitting massive amount of image data via underwater acoustic channel with limited bandwidth. According to the characteristics of underwater color images, an efficient underwater image compression method has been developed. The new coding scheme employs a wavelet-based preprocessing method to remove the visual redundancy, and adopts a Wavelet Tree-based Wavelet Difference Reduction (WTWDR) algorithm to remove the spatial redundancy of underwater color images. Instead of scanning whole transformed image like the WDR method, the difference reduction coding is used for each significant wavelet tree in the proposed WTWDR algorithm based on the correlation between the subbands of higher levels and lower levels of a transformed image. The experimental results show that for underwater color images the proposed method outperforms both WDR and SPIHT at very low bit rates in terms of compression ratio and reconstructed quality, while for natural images it has similar performance with WDR and SPIHT. Hence, the proposed approach is especially suitable for underwater color image compression at very low bit rates.