A5050760333- Remote-Sensing Image Classification
- Remote Sensing and Land Use
- Advanced Image Fusion Techniques
- Remote Sensing in Agriculture
- Image and Signal Denoising Methods
- Image Retrieval and Classification Techniques
- Seismology and Earthquake Studies
- Advanced Image and Video Retrieval Techniques
- Remote Sensing and LiDAR Applications
- Geochemistry and Geologic Mapping
- Earthquake Detection and Analysis
- Medical Image Segmentation Techniques
- Optical and Acousto-Optic Technologies
- earthquake and tectonic studies
- Optical Polarization and Ellipsometry
- Synthetic Aperture Radar (SAR) Applications and Techniques
- Photoacoustic and Ultrasonic Imaging
- Image Enhancement Techniques
- Sparse and Compressive Sensing Techniques
- Seismic Waves and Analysis
- 3D Surveying and Cultural Heritage
- Land Use and Ecosystem Services
- Calibration and Measurement Techniques
- Geophysical Methods and Applications
- Spectroscopy and Chemometric Analyses
Institut polytechnique de Grenoble
2015-2024
Grenoble Images Parole Signal Automatique
2015-2024
Institut Universitaire de France
2021-2024
Université Grenoble Alpes
2015-2024
Centre National de la Recherche Scientifique
2016-2024
The University of Texas at Austin
2024
Institute of Engineering
2023-2024
Centre Inria de l'Université Grenoble Alpes
2023
Tokyo Institute of Technology
2019-2022
Tokyo University of Technology
2019-2022
Pansharpening aims at fusing a multispectral and panchromatic image, featuring the result of processing with spectral resolution former spatial latter. In last decades, many algorithms addressing this task have been presented in literature. However, lack universally recognized evaluation criteria, available image data sets for benchmarking, standardized implementations makes thorough comparison different pansharpening techniques difficult to achieve. paper, authors attempt fill gap by...
Morphological attribute profiles (APs) are defined as a generalization of the recently proposed morphological (MPs). APs provide multilevel characterization an image created by sequential application filters that can be used to model different kinds structural information. According type attributes considered in transformation, parametric features modeled. The generation APs, thanks efficient implementation, strongly reduces computational load required for computation conventional MPs....
In this letter, a technique based on independent component analysis (ICA) and extended morphological attribute profiles (EAPs) is presented for the classification of hyperspectral images. The ICA maps data into subspace in which components are as possible. APs, extracted by using several attributes, applied to each image associated with an component, leading set EAPs. Two approaches including computed analysis. features processing then classified SVM. experiments carried out two images...
Extended attribute profiles and extended multi-attribute are presented for the analysis of hyperspectral high-resolution images. These based on morphological filters and, through a multi-level analysis, capable extracting spatial features that can better model information, with respect to conventional profiles. The extracted by proposed were considered classification task. Two datasets acquired city Pavia, Italy, in analysis. effectiveness introduced operators modelling information was...
Just over a decade has passed since the concept of morphological profile was defined for analysis remote sensing images. Since then, largely proved to be powerful tool able model spatial information (e.g., contextual relations) image. However, due shortcomings using profiles, many variants, extensions, and refinements its definition have appeared stating that is still under continuous development. In this case, recently introduced theoretically sound attribute profiles (APs) can considered...
The pansharpening process has the purpose of building a high-resolution multispectral image by fusing low spatial resolution and panchromatic observations. A very credited method to pursue this goal relies upon injection details extracted from into an upsampled version low-resolution image. In letter, we compare two different methodologies motivate superiority contrast-based methods both physical consideration numerical tests carried out on remotely sensed data acquired IKONOS Quickbird sensors.
Pansharpening refers to the fusion of a multispectral (MS) image and panchromatic (PAN) data aimed at generating an outcome with same spatial resolution PAN spectral MS image. In last 30 years, several approaches deal this issue have been proposed. However, reproducibility these methods is often limited, making comparison state art hard achieve. Thus, fill gap, we propose new benchmark consisting recent advances in pansharpening. particular, optimized classical [multiresolution analysis...
Remote sensing is one of the most common ways to extract relevant information about Earth and our environment. acquisitions can be done by both active (synthetic aperture radar, LiDAR) passive (optical thermal range, multispectral hyperspectral) devices. According sensor, a variety Earth's surface obtained. The data acquired these sensors provide structure (optical, synthetic radar), elevation (LiDAR), material content (multispectral objects in image. Once considered together their...
Nonlinear decomposition schemes constitute an alternative to classical approaches for facing the problem of data fusion. In this paper, we discuss application methodology a popular remote sensing called pansharpening, which consists in fusion low resolution multispectral image and high-resolution panchromatic image. We design complete pansharpening scheme based on use morphological half gradient operators demonstrate suitability algorithm through comparison with state-of-the-art approaches....
In recent years, sparse representations have been widely studied in the context of remote sensing image analysis. this paper, we propose to exploit morphological attribute profiles for remotely sensed classification. Specifically, use extended multiattribute (EMAPs) integrate spatial and spectral information contained data. EMAPs provide a multilevel characterization an created by sequential application filters that can be used model different kinds structural information. Although EMAPs'...
The application of sparse representation (SR) theory to the fusion multispectral (MS) and panchromatic images is giving a large impulse this topic, which recast as signal reconstruction problem from reduced number measurements. This letter presents an effective implementation technique, in SR limited estimation missing details that are injected available MS image enhance its spatial features. We propose algorithm exploiting self-similarity through scales compare it with classical recent...
Extended Attribute Profiles (EAPs), which are obtained by applying morphological attribute filters to an image in a multilevel architecture, can be used for the characterization of spatial characteristics objects scene. EAPs have proved discriminant features when considered thematic classification remote sensing applications especially dealing with very high resolution images. Altimeter data (such as LiDAR) provide important information, being complementary spectral one valuable better...
Classification is one of the most important techniques to analysis hyperspectral remote sensing images. Nonetheless, there are many challenging problems arising in this task. Two common issues curse dimensionality and spatial information modeling. In paper, we present a new general framework train series effective classifiers with for classifying data. The proposed based on two key observations: 1) high feature-to-instance ratio can be alleviated by using random subspace (RS) ensembles; 2)...
Pansharpened images are widely used synthetic representations of the Earth surface characterized by both a high spatial resolution and spectral diversity. They usually generated extracting details from high-resolution PANchromatic image injecting them into low multispectral image. The injection is performed through coefficients, whose values can be either uniform for whole (global methods) or spatially variant (context-adaptive (CA) approaches). In this paper, we propose CA approach in which...
Environmental monitoring is a topic of increasing interest, especially concerning the matter natural hazards prediction. Regarding volcanic unrest, effective methodologies along with innovative and operational tools are needed to monitor, mitigate, prevent risks related hazards. In general, current approaches for volcanoes mainly based on manual analysis various parameters, including gas leaps, deformations measurements, seismic signals analysis. However, due large amount data acquired by in...
Many powerful pansharpening approaches exploit the functional relation between fusion of PANchromatic (PAN) and MultiSpectral (MS) images. To this purpose, modulation transfer function MS sensor is typically used, being easily approximated as a Gaussian filter whose analytic expression fully specified by gain at Nyquist frequency. However, characterization often inadequate in practice. In paper, we develop an algorithm for estimating PAN images directly from available data through efficient...
Morphological and attribute profiles have been proven to be effective tools fuse spectral spatial information for classification of remote sensing data. A wide range filters (i.e., number levels in the profiles) is usually necessary order properly model a scene. dense sampling values parameters generates that both very large dimensionality (leading Hughes phenomenon classification) high redundancy. In this paper, novel iterative technique based on genetic algorithms (GAs) proposed...
Extended attribute profiles, which are based on filters, have recently been presented as efficient tools for spectral-spatial classification of remote sensing images. However, construction these profiles usually requires manual selection parameters the corresponding filters. In this letter, we present a technique to automatically build extended with standard deviation statistics samples belonging classes interest. The methodology is tested two widely used hyperspectral images and results...
The characterization of snow extent is critical for a wide range applications. Since 1966, maps at different spatial resolutions have been produced using various satellite sensor images. Nowadays, the most widely used products are likely those derived from Moderate-Resolution Imaging Spectroradiometer (MODIS) data, which cover whole Earth near-daily frequency. There variety mapping methods MODIS based on methodologies and applied resolutions. Up to now, all these tested evaluated separately....
Comparative evaluation is a requirement for reproducible science and objective assessment of new algorithms. Reproducible research in the field pansharpening very high resolution images difficult task due to lack openly available reference datasets protocols. The contribution this article threefold, it defines benchmarking framework evaluate First, establishes dataset, named PAirMax, composed 14 panchromatic multispectral image pairs collected over heterogeneous landscapes by different...
An unsupervised technique for change detection (CD) in very high geometrical resolution images is proposed, which based on the use of morphological filters. This integrates nonlinear and adaptive properties filters with a vector analysis (CVA) procedure. Different operators are analyzed compared respect to CD problem. Alternating sequential by reconstruction proved be most effective, permitting preservation information structures scene while filtering homogeneous areas. Experimental results...
A new approach to change detection in very high resolution remote sensing images based on morphological attribute profiles (APs) is presented. multiresolution contextual transformation performed by APs allows the extraction of geometrical features related structures within scene at different scales. The temporal changes are detected comparing extracted from image each date. experiments panchromatic QuickBird an urban area show effectiveness proposed technique detecting basis spatial...
The binary partition tree (BPT) is a hierarchical region-based representation of an image in structure. BPT allows users to explore the at different segmentation scales. Often, pruned get more compact and so remaining nodes conform optimal for some given task. Here, we propose novel construction approach pruning strategy hyperspectral images based on spectral unmixing concepts. Linear consists finding signatures materials present (endmembers) their fractional abundances within each pixel....