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Road extraction methods in high-resolution remote sensing images: A comprehensive review
Road extraction from high-resolution remote sensing images is a challenging but hot
research topic in the past decades. A large number of methods are invented to deal with this …
research topic in the past decades. A large number of methods are invented to deal with this …
Beyond pixels: A comprehensive survey from bottom-up to semantic image segmentation and cosegmentation
Image segmentation refers to the process to divide an image into meaningful non-
overlap** regions according to human perception, which has become a classic topic since …
overlap** regions according to human perception, which has become a classic topic since …
Superpixels and polygons using simple non-iterative clustering
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 …
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 …
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 …
Superpixel segmentation using linear spectral clustering
We present in this paper a superpixel segmentation algorithm called Linear Spectral
Clustering (LSC), which produces compact and uniform superpixels with low computational …
Clustering (LSC), which produces compact and uniform superpixels with low computational …
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 …
Real-time superpixel segmentation by DBSCAN clustering algorithm
In this paper, we propose a real-time image superpixel segmentation method with 50
frames/s by using the density-based spatial clustering of applications with noise (DBSCAN) …
frames/s by using the density-based spatial clustering of applications with noise (DBSCAN) …
Transmission estimation in underwater single images
This paper proposes a methodology to estimate the transmission in underwater
environments which consists on an adaptation of the Dark Channel Prior (DCP), a statistical …
environments which consists on an adaptation of the Dark Channel Prior (DCP), a statistical …
Geodesic saliency using background priors
Generic object level saliency detection is important for many vision tasks. Previous
approaches are mostly built on the prior that “appearance contrast between objects and …
approaches are mostly built on the prior that “appearance contrast between objects and …