Recent development of feature extraction and classification multispectral/hyperspectral images: a systematic literature review

International Conference on Computing and Applied Informatics 2016

物理学;计算机科学

Setiyoko, A.^1,2 ; Dharma, I.G.W.S.^1 ; Haryanto, T.^1

Faculty of Computer Science, University of Indonesia, Depok, Indonesia^1

Remote Sensing Technology and Data Center-LAPAN, Jl Lapan 70, Pekayon, Pasar Rebo, Jakarta Timur

13710, Indonesia^2

关键词: Classification process;    Computational costs;    Feature extraction and classification;    Feature extraction techniques;    Geo-spatial informations;    Hyperspectral Data;    Multi-spectral data;    Systematic literature review;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/801/1/012045/pdf
DOI  :  10.1088/1742-6596/801/1/012045

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

Multispectral data and hyperspectral data acquired from satellite sensor have the ability in detecting various objects on the earth ranging from low scale to high scale modeling. These data are increasingly being used to produce geospatial information for rapid analysis by running feature extraction or classification process. Applying the most suited model for this data mining is still challenging because there are issues regarding accuracy and computational cost. This research aim is to develop a better understanding regarding object feature extraction and classification applied for satellite image by systematically reviewing related recent research projects. A method used in this research is based on PRISMA statement. After deriving important points from trusted sources, pixel based and texture-based feature extraction techniques are promising technique to be analyzed more in recent development of feature extraction and classification.