Mahamadou Idrissa's research while affiliated with Royal Military Academy and other places

Publications (18)

Conference Paper
Full-text available
Mapping the urban land cover from VHR optical imagery remains a challenging task, more particularly in cities that present complex landscapes and patterns. In this study, we assessed the contribution of height data derived from WorldView-3 stereo imagery for mapping the land cover of Sub-Saharan African cities. Our case study is located in Ouagadou...
Article
Digital terrain models (DTMs) are of significant interest for applications such as environment planning, flood risk assessment or building detection. A digital surface model (DSM) can be obtained efficiently in both time and cost from light detection and ranging (lidar) acquisition or from digital photogrammetry with aerial or satellite stereoscopi...
Article
Epipolar rectification aims at resampling stereoscopic images so that conjugate points are located along the same horizontal x-axis. For most stereoscopic digital surface model production algorithms, this rectification is a necessary preprocessing task because it allows reducing the 2D matching to a 1D matching problem. Most epipolar rectification...
Conference Paper
Very high resolution multispectral imaging reached a high level of reliability and accuracy for target detection and classification. However, in an urban scene, the complexity is raised, making the detection and the identification of small objects difficult. One way to overcome this difficulty is to combine spectral information with 3D data. A set...
Conference Paper
This paper deals with building change detection by supervised classification of image regions into ’built’ and ’non-built’ areas. Regions are the connected components of low gradient values in a multi-spectral aerial image. Classes are learnt from spectral (colour, vegetation index) and elevation cues relatively to building polygons and non buildin...
Article
This paper presents a supervised classification method applied to building change detection in VHR aerial images. Multi-spectral stereo pairs of 0.3m resolution have been processed to derive elevation, vegetation index and colour features. These features help filling a 5-dimensional histogram whose bins finally hold the ratio of built-up and non bu...
Article
The proposed scanned graphics palette extraction process starts with the extraction of colors of uniform regions, then the colors of local features. In order to enhance the discrimination of unsaturated colors, the image is converted into L*a*b* space and the CMC color difference is used together with the Euclidean distance. After the palette extra...
Conference Paper
We present a method that reduces the computational cost of the MRF-based stereo algorithm and increases the quality of the final disparity map. In a first step, using window-based method we compute successive disparity maps at different resolutions by varying the correlation window size, in order to estimate for each pixel the set of most probable...
Conference Paper
Change detection of remotely sensed images is a particularly challenging task when the available data come from different sensors. Indeed, many change indicators are based on radiometry measures, operating on their differences or ratios, that are no longer reliable when the data have been acquired by different instruments. For this reason, it is in...
Conference Paper
Change detection of remotely sensed images is a particularly challenging task when the available data come from different sensors. Indeed, many change indicators are based on radiometry measures, operating on them differences or ratios, that are no longer reliable when the data have been acquired by different instruments. For this reason, it is int...
Article
An automatic system to estimate the urbanization changes on the Belgian territory, using SPOT5 images and the National Geo- graphic Institute vectorial database is proposed. The images and the vectorial data are first co-registered. Then, the vectorial database is projected and dilated to produce a mask representing the old status of the database....
Article
An automatic system to estimate the urbanization changes on the Belgian territory, using SPOT5 images and the National Geographic Institute vectorial database is proposed. The images and the vectorial data are first co-registered. Then, the vectorial database is projected and dilated to produce a mask representing the old status of the database. On...
Article
Introduction PARADIS stands for a Prototype for Assisting Rational Activities in Demining using Images from Satellites. The aim of this project is to improve the planning of humanitarian demining campaigns using Remote Sensing data and GIS techniques. In this context, a user interface has been developed in ArcView GIS to integrate the tools needed...
Article
An unsupervised texture classification scheme is proposed in this paper. The texture features are based on the image local spectrum which is obtained by a bank of Gabor filters. The fuzzy clustering algorithm is used for unsupervised classification. In many applications, this algorithm depends on assumptions made about the number of subgroups prese...
Article
Full-text available
Introduction PARADIS stands for a Prototype for Assisting Rational Activities in Demining using Images from Satellites. The aim of this project is to improve the planning of humanitarian demining campaigns using Remote Sensing data and GIS techniques. In this context, a user interface has been developed in ArcView GIS to integrate the tools needed...
Article
The aim of the ETATS project ("Systeme d'Evaluation du Taux d'Actualisation de donnees topog´ eographiques par T´ eled´ etection Spatiale") is to estimate the degree of changes in the built-up area and in the communication network for the Belgian terri- tory, using satellite images and the National Geographic Institute database. SPOT5 images have b...

Citations

... Therefore, in terms of accuracy changes, there was not a large impact of the reduced variable number on buildings, forests, and street-trees, corroborating the use of nDSM and NDVI in previous studies to accurately classify buildings and forests [55][56][57]. Vanhuysse et al. [58] reported that when nDSM was used as input data, there were improvements in the quantitative and qualitative analysis of building and other classification results. Therefore, in the present study, buildings, forests, and street-trees showed little change despite variable optimization, as nDSM and NDVI, which occupied high ranks of variable importance, were included. ...
... NDVI suffers from the poor spectral resolution in the shadow areas where most objects appear greyish so that the NDVI tends to 0. Therefore, the landslides detected by NDVI might be overestimated in the shadow areas (Beumier and Idrissa, 2014). Different screening indexes, including brightness (Hsieh et al., 2011), greenness (Liu et al., 2012;Lin et al., 2013), and vegetation mask (Beumier and Idrissa, 2014), were cou- 15 pled with the NDVI criteria to improve the accuracy of landslide identification in shadow areas. ...
... In recent years, with the rapid development of aerospace technology, remote sensing imagery analysis for high-resolution images acquired by aerial or satellite sensors has received extensive attention. Learning height information from single aerial images, being one of the important tasks in remote sensing imagery analysis, can provide geometric information for 3D reconstruction of ground scenes, and is widely used in a variety of applications, such as urban planning [1], change detection [2], and disaster monitoring [3]. Recently, thriving deep learning technology has made tremendous progress in the photogrammetry and remote sensing communities [4][5][6][7]. ...
... To realize the epipolar resampling of push-broom satellite images, researchers have done a lot of work [16][17][18]. However, these work mainly focus on the epipolar resampling of stereo pairs, which are obtained with designed stereo angles and radiative conditions. ...
... These methods have gradually evolved from pixel-oriented to object-oriented techniques. Specifically, these methods and models involve the identification of uniform regions [4], watershed segmentation [5], morphological index [6], [7], clustering extraction of urban changes [8]- [10], bottom-up and top-down hybrid algorithms [11], and simple geometric structure methods [12]. Further, regarding multitarget change detection, Jabari et al. [13] proposed a change criterion that uses multivariate expansion to overcome nonlinear imaging condition differences and that utilizes multispectral properties for optical change detection. ...
... persons, vehicles and objects). The processing covers classification, anomaly detection, change detection and spectral matching [3,4,5]. The processing used hyperspectral data from the visible light to the short wave infrared data and in the long wave infrared, broad band sensor data in the visible, near infrared and mid wave infrared and airborne 3D-laser scanner as well. ...
... First, we introduce a histogram-based classification algorithm to associate an opinion distribution with a qualitative category. Histogram-based classification has been used in many fields, especially related to image processing 30,31 ; yet, to the best of our knowledge, this is the first time it is adopted in an opinion-dynamics setting. Second, we construct a transition table to visualize how opinion distributions evolve over time from an initial to a possibly different final qualitative category. ...
... Therefore, it seems to be a smart idea to divide the metropolitan/urban area into parts and to detect buildings in them separately. The location of buildings can be detected in these areas by using a novel probabilistic framework such as Gabor filter [16][17][18]. Gabor filter is a band-pass filter selective to both orientation and spatial frequency. It is suitable for detecting local structural patterns from images and has been widely applied to texture analysis and object recognition. ...
... Due to misinterpretations caused by ambient light and shadow as well as sensor geometry, matching feature pixels in a stereo pair presents a challenge. Feature detection methods that initially detect pronounced features in images (e.g., corners, high entropy regions, scale space maxima, etc.), following local approaches [19][20][21] have demonstrated considerable success in a variety of applications such as object recognition [22], wide-base line stereo [23], robot navigation [24], content-based image retrieval [25,26], image stitching for panorama construction [27], etc. The Scale-Invariant Feature Transform (SIFT) proposed by [22,28] is probably the most popular and widely used local approach [29]. ...