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Segmentation for Object-Based Image Analysis (OBIA): A review of algorithms and challenges from remote sensing perspective
Image segmentation is a critical and important step in (GEographic) Object-Based Image
Analysis (GEOBIA or OBIA). The final feature extraction and classification in OBIA is highly …
Analysis (GEOBIA or OBIA). The final feature extraction and classification in OBIA is highly …
A review of accuracy assessment for object-based image analysis: From per-pixel to per-polygon approaches
Object-based image analysis (OBIA) has gained widespread popularity for creating maps
from remotely sensed data. Researchers routinely claim that OBIA procedures outperform …
from remotely sensed data. Researchers routinely claim that OBIA procedures outperform …
[HTML][HTML] Deep-learning Versus OBIA for Scattered Shrub Detection with Google Earth Imagery: Ziziphus lotus as Case Study
There is a growing demand for accurate high-resolution land cover maps in many fields, eg,
in land-use planning and biodiversity conservation. Develo** such maps has been …
in land-use planning and biodiversity conservation. Develo** such maps has been …
Remote sensing imagery segmentation in object-based analysis: A review of methods, optimization, and quality evaluation over the past 20 years
Object-based image analysis (OBIA) has become a key research topic for decades and
represents an attractive paradigm leading to accurate features classification and recognition …
represents an attractive paradigm leading to accurate features classification and recognition …
Supervised methods of image segmentation accuracy assessment in land cover map**
Land cover map** via image classification is sometimes realized through object-based
image analysis. Objects are typically constructed by partitioning imagery into spatially …
image analysis. Objects are typically constructed by partitioning imagery into spatially …
Performance evaluation of object based greenhouse detection from Sentinel-2 MSI and Landsat 8 OLI data: A case study from Almería (Spain)
This paper shows the first comparison between data from Sentinel-2 (S2) Multi Spectral
Instrument (MSI) and Landsat 8 (L8) Operational Land Imager (OLI) headed up to …
Instrument (MSI) and Landsat 8 (L8) Operational Land Imager (OLI) headed up to …
Improving building rooftop segmentation accuracy through the optimization of UNet basic elements and image foreground-background balance
J Yang, B Matsushita, H Zhang - ISPRS Journal of Photogrammetry and …, 2023 - Elsevier
Building rooftop segmentation using deep learning techniques is a popular yet challenging
area of research in computer vision and remote sensing image processing. While recent …
area of research in computer vision and remote sensing image processing. While recent …
Segmentation quality evaluation using region-based precision and recall measures for remote sensing images
Segmentation of remote sensing images is a critical step in geographic object-based image
analysis. Evaluating the performance of segmentation algorithms is essential to identify …
analysis. Evaluating the performance of segmentation algorithms is essential to identify …
A multi-index learning approach for classification of high-resolution remotely sensed images over urban areas
In recent years, it has been widely agreed that spatial features derived from textural,
structural, and object-based methods are important information sources to complement …
structural, and object-based methods are important information sources to complement …
Optimizing multi-resolution segmentation scale using empirical methods: Exploring the sensitivity of the supervised discrepancy measure Euclidean distance 2 (ED2)
Multiresolution segmentation (MRS) has proven to be one of the most successful image
segmentation algorithms in the geographic object-based image analysis (GEOBIA) …
segmentation algorithms in the geographic object-based image analysis (GEOBIA) …