Object-Based Change Detection in Urban Areas: The Effects of Segmentation Strategy, Scale, and Feature Space on Unsupervised Methods [PDF]
Remote Sensing, 2016 Object-based change detection (OBCD) has recently been receiving increasing attention as a result of rapid improvements in the resolution of remote sensing data.
Lei Ma +7 more
doaj +3 more sources
Multiresolution segmentation of natural images: from linear to nonlinear scale-space representations [PDF]
IEEE Transactions on Image Processing, 2004 In this paper, we introduce a framework that merges classical ideas borrowed from scale-space and multiresolution segmentation with nonlinear partial differential equations. A non-linear scale-space stack is constructed by means of an appropriate diffusion equation.
Petrovic, A. +2 more
semanticscholar +5 more sources
FarSee-Net: Real-Time Semantic Segmentation by Efficient Multi-scale Context Aggregation and Feature Space Super-resolution [PDF]
IEEE International Conference on Robotics and Automation, 2020 Real-time semantic segmentation is desirable in many robotic applications with limited computation resources. One challenge of semantic segmentation is to deal with the object scale variations and leverage the context.
Zhanpeng Zhang, Kaipeng Zhang
semanticscholar +5 more sources
Multi-Scale Deep Neural Network Based on Dilated Convolution for Spacecraft Image Segmentation
Sensors, 2022 In recent years, image segmentation techniques based on deep learning have achieved many applications in remote sensing, medical, and autonomous driving fields.
Yuan Liu +5 more
doaj +2 more sources
A parameterless scale-space approach to find meaningful modes in histograms - Application to image and spectrum segmentation [PDF]
Int. J. Wavelets Multiresolution Inf. Process., 2014 In this paper, we present an algorithm to automatically detect meaningful modes in a histogram. The proposed method is based on the behavior of local minima in a scale-space representation.
J. Gilles, K. Heal
semanticscholar +5 more sources
A NEW FRAMEWORK FOR OBJECT-BASED IMAGE ANALYSIS BASED ON SEGMENTATION SCALE SPACE AND RANDOM FOREST CLASSIFIER [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2015 In this paper a new object-based framework is developed for automate scale selection in image segmentation. The quality of image objects have an important impact on further analyses.
A. Hadavand +2 more
doaj +3 more sources
Remote SensingSemantic segmentation of urban meshes plays an increasingly crucial role in the analysis and understanding of 3D environments. Most existing large-scale urban mesh semantic segmentation methods focus on integrating multi-scale local features but struggle
Wenjie Zi +3 more
doaj +2 more sources
SensorsStreet trees are of great importance to urban green spaces. Quick and accurate segmentation of street trees from high-resolution remote sensing images is of great significance in urban green space management. However, traditional segmentation methods can
Hongyang Zhang, Shuo Liu
doaj +2 more sources
A scale space based algorithm for automated segmentation of single shot tagged MRI of shearing deformation [PDF]
Magnetic Resonance Materials in Physics, Biology and Medicine, 2013 ObjectThis study proposes a scale space based algorithm for automated segmentation of single-shot tagged images of modest SNR. Furthermore the algorithm was designed for analysis of discontinuous or shearing types of motion, i.e.
A. Sprengers +5 more
semanticscholar +2 more sources
IEEE Access, 2020 Land cover segmentation is an important and challenging task in the field of remote sensing. Even though convolutional neural networks (CNNs) provide great support for semantic segmentation, standard models are still difficult to capture global ...
Shuyang Wang +4 more
doaj +2 more sources