Morphological representation of DCT coefficients for image compression

Debin Zhao; Wen Gao; Y. K. Chan

doi:10.1109/TCSVT.2002.803218

Morphological representation of DCT coefficients for image compression

Debin Zhao
, Wen Gao
, Y. K. Chan

Department of Computer Science

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

32 Citations (Scopus)

Abstract

Recent success in discrete cosine transform (DCT) image coding is mainly attributed to recognition of the importance of data organization and representation. Currently, there are several competitive DCT-based coders such as Xiong et al. DCT-based embedded image coding (EZDCT) and Davis and Chawla's significance tree quantization (STQ). In the wavelet context, morphological representation of wavelet data has achieved the best compression performance. The representatives are Servetto et al. morphological representation of wavelet data (MRWD) and Chai et al. significance-linked connected component analysis. In this paper, we show that the block-based DCT by proper reorganization of its coefficients can have similar characteristics to wavelet transform, such as energy compaction, cross-subband similarity, decay of magnitude across subband, etc. These characteristics can widen DCT applications relevant to image compression, image retrieving, pattern recognition, etc. We then present an image coder utilizing these characteristics by morphological representation of DCT coefficients (MRDCT). The experiments show that MRDCT is among the state-of-the-art DCT-based image coders reported in the literature. For example, for the Lena image at 0.25 bpp, MRDCT outperforms JPEG, STQ, and EZDCT by 1.0, 1.0, and 0.3 dB in peak signal-to-noise ratio, respectively.
© 2002 IEEE

Original language	English
Pages (from-to)	819-823
Journal	IEEE Transactions on Circuits and Systems for Video Technology
Volume	12
Issue number	9
DOIs	https://doi.org/10.1109/TCSVT.2002.803218
Publication status	Published - Sept 2002

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

Funding

This work was supported by the University Grant Council of Hong Kong and by the Cooperative Research Center, City University of Hong Kong, under Contract 8720002 and by the 100 Outstanding Scientists Foundation of Chinese Academy of Sciences. This paper was recommended by Associate Editor S. U. Lee.

Research Keywords

Data compression
Discrete cosine transform
Image coding
Morphological representation

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10.1109/TCSVT.2002.803218

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title = "Morphological representation of DCT coefficients for image compression",

abstract = "Recent success in discrete cosine transform (DCT) image coding is mainly attributed to recognition of the importance of data organization and representation. Currently, there are several competitive DCT-based coders such as Xiong et al. DCT-based embedded image coding (EZDCT) and Davis and Chawla's significance tree quantization (STQ). In the wavelet context, morphological representation of wavelet data has achieved the best compression performance. The representatives are Servetto et al. morphological representation of wavelet data (MRWD) and Chai et al. significance-linked connected component analysis. In this paper, we show that the block-based DCT by proper reorganization of its coefficients can have similar characteristics to wavelet transform, such as energy compaction, cross-subband similarity, decay of magnitude across subband, etc. These characteristics can widen DCT applications relevant to image compression, image retrieving, pattern recognition, etc. We then present an image coder utilizing these characteristics by morphological representation of DCT coefficients (MRDCT). The experiments show that MRDCT is among the state-of-the-art DCT-based image coders reported in the literature. For example, for the Lena image at 0.25 bpp, MRDCT outperforms JPEG, STQ, and EZDCT by 1.0, 1.0, and 0.3 dB in peak signal-to-noise ratio, respectively. {\textcopyright} 2002 IEEE",

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AU - Gao, Wen

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N2 - Recent success in discrete cosine transform (DCT) image coding is mainly attributed to recognition of the importance of data organization and representation. Currently, there are several competitive DCT-based coders such as Xiong et al. DCT-based embedded image coding (EZDCT) and Davis and Chawla's significance tree quantization (STQ). In the wavelet context, morphological representation of wavelet data has achieved the best compression performance. The representatives are Servetto et al. morphological representation of wavelet data (MRWD) and Chai et al. significance-linked connected component analysis. In this paper, we show that the block-based DCT by proper reorganization of its coefficients can have similar characteristics to wavelet transform, such as energy compaction, cross-subband similarity, decay of magnitude across subband, etc. These characteristics can widen DCT applications relevant to image compression, image retrieving, pattern recognition, etc. We then present an image coder utilizing these characteristics by morphological representation of DCT coefficients (MRDCT). The experiments show that MRDCT is among the state-of-the-art DCT-based image coders reported in the literature. For example, for the Lena image at 0.25 bpp, MRDCT outperforms JPEG, STQ, and EZDCT by 1.0, 1.0, and 0.3 dB in peak signal-to-noise ratio, respectively. © 2002 IEEE

AB - Recent success in discrete cosine transform (DCT) image coding is mainly attributed to recognition of the importance of data organization and representation. Currently, there are several competitive DCT-based coders such as Xiong et al. DCT-based embedded image coding (EZDCT) and Davis and Chawla's significance tree quantization (STQ). In the wavelet context, morphological representation of wavelet data has achieved the best compression performance. The representatives are Servetto et al. morphological representation of wavelet data (MRWD) and Chai et al. significance-linked connected component analysis. In this paper, we show that the block-based DCT by proper reorganization of its coefficients can have similar characteristics to wavelet transform, such as energy compaction, cross-subband similarity, decay of magnitude across subband, etc. These characteristics can widen DCT applications relevant to image compression, image retrieving, pattern recognition, etc. We then present an image coder utilizing these characteristics by morphological representation of DCT coefficients (MRDCT). The experiments show that MRDCT is among the state-of-the-art DCT-based image coders reported in the literature. For example, for the Lena image at 0.25 bpp, MRDCT outperforms JPEG, STQ, and EZDCT by 1.0, 1.0, and 0.3 dB in peak signal-to-noise ratio, respectively. © 2002 IEEE

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KW - Discrete cosine transform

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Morphological representation of DCT coefficients for image compression

Abstract

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