Evaluating the Effects of Image Texture Analysis on Plastic Greenhouse Segments via Recognition of the OSI-USI-ETA-CEI Pattern

摘要: Compared to multispectral or panchromatic bands, fusion imagery contains both the spectral content of former and spatial resolution latter. Even though Estimation Scale Parameter (ESP), ESP 2 tool, some segmentation evaluation methods have been introduced simplify choice scale parameter (SP), shape, compactness, many challenges remain, including obtaining natural border plastic greenhouses (PGs) from a GaoFen-2 (GF-2) imagery, accelerating progress follow-up texture analysis, accurately evaluating over-segmentation under-segmentation PG segments in geographic object-based image analysis. Considering features high-resolution images, heterogeneity was compressed using analysis before calculating optimal this study. As result, we quantified effects increasing averaging operator size (AOS) decreasing greyscale quantization level (GQL) on via recognition proposed Over-Segmentation Index (OSI)-Under-Segmentation (USI)-Error Total Area (ETA)-Composite Error (CEI) pattern. The pattern can be used reasonably evaluate quality obtained GF-2 its derivative showing that appropriate effectively change for better segmentation. optimum setup GQL AOS are determined by comparing CEI visual