Advances in mathematical morphology applied to geoscience and remote sensing
P Soille, M Pesaresi - IEEE Transactions on Geoscience and …, 2002 - ieeexplore.ieee.org
By concentrating on the analysis of the spatial relationships between groups of pixels,
mathematical morphology provides us with an image processing strategy complementary to …
mathematical morphology provides us with an image processing strategy complementary to …
Forest volume and biomass estimation using small-footprint lidar-distributional parameters on a per-segment basis
This study assessed a lidar-based, object-oriented (segmentation) approach to forest
volume and aboveground biomass modeling. The study area in the Piedmont physiographic …
volume and aboveground biomass modeling. The study area in the Piedmont physiographic …
Region-level SAR image segmentation based on edge feature and label assistance
This article proposes a novel segmentation algorithm for synthetic aperture radar (SAR)
images. The algorithm performs region-level segmentation based on edge feature and label …
images. The algorithm performs region-level segmentation based on edge feature and label …
SAR image segmentation based on constrained smoothing and hierarchical label correction
Synthetic aperture radar (SAR) is widely used in the field of modern remote sensing due to
its high resolution for a comparatively small antenna. However, there are still some …
its high resolution for a comparatively small antenna. However, there are still some …
[图书][B] Remote sensing of coastal environments
Y Wang - 2009 - taylorfrancis.com
As coastal environments around the world face unprecedented natural and anthropogenic
threats, advancements in the technologies that support geospatial data acquisition, imaging …
threats, advancements in the technologies that support geospatial data acquisition, imaging …
Context-based hierarchical unequal merging for SAR image segmentation
This paper presents an image segmentation method named Context-based Hierarchical
Unequal Merging for Synthetic aperture radar (SAR) Image Segmentation (CHUMSIS) …
Unequal Merging for Synthetic aperture radar (SAR) Image Segmentation (CHUMSIS) …
TSPol-ASLIC: Adaptive superpixel generation with local iterative clustering for time-series quad-and dual-polarization SAR data
The superpixel generation is a key step for object-based classification and change
detection. For the time-series polarimetric synthetic aperture radar (PolSAR) superpixel …
detection. For the time-series polarimetric synthetic aperture radar (PolSAR) superpixel …
A framework of region-based spatial relations for non-overlapping features and its application in object based image analysis
Object based image analysis (OBIA) is an approach increasingly used in classifying high
spatial resolution remote sensing images. Object based image classifiers first segment an …
spatial resolution remote sensing images. Object based image classifiers first segment an …
Extraction of impervious surface areas from high spatial resolution imagery by multiple agent segmentation and classification
In recent years impervious surface areas (ISA) have emerged as a key paradigm to explain
and predict ecosystem health in relationship to watershed development. The ISA data are …
and predict ecosystem health in relationship to watershed development. The ISA data are …
Adaptive hybrid conditional random field model for SAR image segmentation
F Wang, Y Wu, M Li, P Zhang… - IEEE Transactions on …, 2016 - ieeexplore.ieee.org
For random-field-based image segmentation, the conditional random field (CRF) model
offers theoretic advantages over the generative Markov random field one, since it directly …
offers theoretic advantages over the generative Markov random field one, since it directly …