Adaptive method of process flow parameter values setting based on remote sensing image metadata

Bing Zhou; Jian kang Ge; Xianyu Zuo

doi:10.1117/12.2674321

28 April 2023 Adaptive method of process flow parameter values setting based on remote sensing image metadata

Bing Zhou, Jian kang Ge, Xianyu Zuo

Proceedings Volume 12626, International Conference on Signal Processing, Computer Networks, and Communications (SPCNC 2022); 126260D (2023) https://doi.org/10.1117/12.2674321
Event: International Conference on Signal Processing, Computer Networks, and Communications (SPCNC 2022), 2022, Zhuhai, China

Abstract

Remote sensing data processing involves many steps. This paper uses process flow to represent these processing steps. This paper combines remote sensing image metadata (RSIM) with case based reasoning (CBR) technology, proposes a parameter value adaptive method based on RSIM, and constructs a remote RSIM case model. It makes the representation of RSIM more intuitive and convenient. This method consists of two parts: case building and case similarity measurement. Case building refers to building RSIM into RSIM cases according to case models, and then classifying and saving each case. Case similarity measurement refers to the similarity measurement of metadata in the production process and each case under the flow. Finally, the parameter values will be configured according to the highest similarity. The method is tested in an actual remote sensing production system, and the experimental results show that the method has good applicability in the parameter value adaptation of remote sensing process production.

Citation Download Citation

Bing Zhou, Jian kang Ge, and Xianyu Zuo "Adaptive method of process flow parameter values setting based on remote sensing image metadata", Proc. SPIE 12626, International Conference on Signal Processing, Computer Networks, and Communications (SPCNC 2022), 126260D (28 April 2023); https://doi.org/10.1117/12.2674321

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