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Conference Paper: TIME SERIES MODELING FOR TEXTURE ANALYSIS AND SYNTHESIS WITH APPLICATIONS TO CLOUD FIELD MORPHOLOGY STUDY.
Title | TIME SERIES MODELING FOR TEXTURE ANALYSIS AND SYNTHESIS WITH APPLICATIONS TO CLOUD FIELD MORPHOLOGY STUDY. |
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Authors | |
Keywords | INFORMATION THEORY - Data Compression |
Issue Date | 1984 |
Citation | Proceedings - International Conference on Pattern Recognition, 1984, v. 2, p. 1219-1221 How to Cite? |
Abstract | This paper presents a procedure to model texture fields using seasonal autoregressive, moving average models. The modeling of 2-D images has been formulated as a 1-D time series analysis problem. Properties such as directionality and clustering have been fully investigated and presented. The applications of this 1-D seasonal ARMA process to texture analysis, synthesis and data compression have been discussed. It was demonstrated that a cloud field image can be quantitatively defined and its surrogates can be synthesized by the model parameters. The implications for the quantitative study of cloud climatology is thus evident. |
Persistent Identifier | http://hdl.handle.net/10722/65576 |
DC Field | Value | Language |
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dc.contributor.author | Jau, YingChia | en_HK |
dc.contributor.author | Chin, Roland T | en_HK |
dc.contributor.author | Weinman, James A | en_HK |
dc.date.accessioned | 2010-08-31T07:16:14Z | - |
dc.date.available | 2010-08-31T07:16:14Z | - |
dc.date.issued | 1984 | en_HK |
dc.identifier.citation | Proceedings - International Conference on Pattern Recognition, 1984, v. 2, p. 1219-1221 | en_HK |
dc.identifier.uri | http://hdl.handle.net/10722/65576 | - |
dc.description.abstract | This paper presents a procedure to model texture fields using seasonal autoregressive, moving average models. The modeling of 2-D images has been formulated as a 1-D time series analysis problem. Properties such as directionality and clustering have been fully investigated and presented. The applications of this 1-D seasonal ARMA process to texture analysis, synthesis and data compression have been discussed. It was demonstrated that a cloud field image can be quantitatively defined and its surrogates can be synthesized by the model parameters. The implications for the quantitative study of cloud climatology is thus evident. | en_HK |
dc.language | eng | en_HK |
dc.relation.ispartof | Proceedings - International Conference on Pattern Recognition | en_HK |
dc.subject | INFORMATION THEORY - Data Compression | en_HK |
dc.title | TIME SERIES MODELING FOR TEXTURE ANALYSIS AND SYNTHESIS WITH APPLICATIONS TO CLOUD FIELD MORPHOLOGY STUDY. | en_HK |
dc.type | Conference_Paper | en_HK |
dc.identifier.email | Chin, Roland T: rchin@hku.hk | en_HK |
dc.identifier.authority | Chin, Roland T=rp01300 | en_HK |
dc.description.nature | link_to_subscribed_fulltext | en_HK |
dc.identifier.scopus | eid_2-s2.0-0021632820 | en_HK |
dc.identifier.volume | 2 | en_HK |
dc.identifier.spage | 1219 | en_HK |
dc.identifier.epage | 1221 | en_HK |
dc.identifier.scopusauthorid | Jau, YingChia=6602782713 | en_HK |
dc.identifier.scopusauthorid | Chin, Roland T=7102445426 | en_HK |
dc.identifier.scopusauthorid | Weinman, James A=7101645308 | en_HK |