Open AccessResearch Progress in Remote Sensing Image Texture Analysis
Author(s) -
Chuen-Tsai Sun,
Zhen Wen
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1961/1/012028
Subject(s) - computer science , image texture , artificial intelligence , texture (cosmology) , wavelet , sorting , texture compression , feature extraction , process (computing) , computer vision , texture filtering , image (mathematics) , pattern recognition (psychology) , remote sensing , image processing , geography , algorithm , operating system
Current remote sensing image texture analysis and research is based texture feature. Specialist, who home and abroad, has been continuously explore an optimal extraction process and texture analyze method or through a variety of methods to realize extraction of remote sensing texture information. There are three directions, which including the research of optimal scale, the fusion of method, the proposal and improvement of new algorithm, could comprehensive summary about recent research progress in remote sensing image texture analysis by sorting and analyzing information extraction of remote sensing texture features, the progress of texture analysis methods and the application of analysis methods in recent years. At the same time, a prediction was made for future development of remote sensing image texture analysis. Five development directions are summarized: fusion method, scale selection, continuation and improvement of traditional methods based on symbiotic gray matrix and wavelet analysis, research and exploration of object-oriented and deep learning methods, and research of new algorithms to improve the information extraction effect.