Segmentation for Object-Based Image Analysis (OBIA): A review of algorithms and challenges from remote sensing perspective
MD Hossain, D Chen - ISPRS Journal of Photogrammetry and Remote …, 2019 - Elsevier
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 …
Salient object detection: A survey
Detecting and segmenting salient objects from natural scenes, often referred to as salient
object detection, has attracted great interest in computer vision. While many models have …
object detection, has attracted great interest in computer vision. While many models have …
Superpixel segmentation with fully convolutional networks
In computer vision, superpixels have been widely used as an effective way to reduce the
number of image primitives for subsequent processing. But only a few attempts have been …
number of image primitives for subsequent processing. But only a few attempts have been …
Superpixels: An evaluation of the state-of-the-art
Superpixels group perceptually similar pixels to create visually meaningful entities while
heavily reducing the number of primitives for subsequent processing steps. As of these …
heavily reducing the number of primitives for subsequent processing steps. As of these …
Superpixels and polygons using simple non-iterative clustering
R Achanta, S Susstrunk - Proceedings of the IEEE …, 2017 - openaccess.thecvf.com
We present an improved version of the Simple Linear Iterative Clustering (SLIC) superpixel
segmentation. Unlike SLIC, our algorithm is non-iterative, enforces connectivity from the …
segmentation. Unlike SLIC, our algorithm is non-iterative, enforces connectivity from the …
Robust nucleus/cell detection and segmentation in digital pathology and microscopy images: a comprehensive review
Digital pathology and microscopy image analysis is widely used for comprehensive studies
of cell morphology or tissue structure. Manual assessment is labor intensive and prone to …
of cell morphology or tissue structure. Manual assessment is labor intensive and prone to …
SuperPCA: A superpixelwise PCA approach for unsupervised feature extraction of hyperspectral imagery
As an unsupervised dimensionality reduction method, the principal component analysis
(PCA) has been widely considered as an efficient and effective preprocessing step for …
(PCA) has been widely considered as an efficient and effective preprocessing step for …
Superpixel sampling networks
Superpixels provide an efficient low/mid-level representation of image data, which greatly
reduces the number of image primitives for subsequent vision tasks. Existing superpixel …
reduces the number of image primitives for subsequent vision tasks. Existing superpixel …
SLIC superpixels compared to state-of-the-art superpixel methods
Computer vision applications have come to rely increasingly on superpixels in recent years,
but it is not always clear what constitutes a good superpixel algorithm. In an effort to …
but it is not always clear what constitutes a good superpixel algorithm. In an effort to …