Detecting information under and from shadow in panchromatic Ikonos images of the city of Sherbrooke

Massalabi, A.; He, Dong-Chen; Bénié, G.B.; Beaudry, Éric

doi:10.1109/igarss.2004.1370740

Cited by 15 publications

(13 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Moreover in [20], the concept of pattern spectrum was extended by defining scale invariant pattern spectra obtained with shape attributes. If the criterion is increasing, then (6) and (7) are equal to (5). Similar conclusions can be drawn for attribute closing and thickening.…”

Section: Thinningsupporting

confidence: 62%

“…This solution leads the grayscale attribute thinning (see (5)) that operates on an image by removing a connected component C if its attribute does not fulfill the criterion and nor holds for the regions included by C. In [19] this filtering strategy was referred to as max rule. However, other arbitrary filtering strategies can be implemented in order to achieve different output effects when extending the binary thinning and thickening to numerical images [19,20].…”

Section: Thinningmentioning

confidence: 99%

“…In particular most of the researches in this field are mainly focused on retrieving the height of the buildings from SAR images [1][2] [3], or from the fusion of SAR and high resolution optical images [4]. Besides the use of SAR images, retrieving the height of the buildings from optical data is not a trivial task, because the height information can be extracted only by investigating the effects of the buildings on the surroundings, such as by measuring the shadows produced by the buildings themselves [5]. However this kind of approaches cannot be accurate because they do not take into account the relative height of the surrounding environment.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Retrieval of the Height of Buildings From WorldView-2 Multi-Angular Imagery Using Attribute Filters and Geometric Invariant Moments

Licciardi

Villa

Mura

et al. 2012

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

View full text Add to dashboard Cite

This paper proposes a novel approach to the retrieval of buildings' height from multi-angular high spatial resolution images. To achieve this task, we combined two main concepts: multilevel morphological attribute filters, used for the definition of the objects in the image, and geometric invariant moments exploited for the characterization of the spatial properties of the previously detected shapes. The main concept of this study relies on the spatial properties of very high resolution images acquired from different angles of view. In particular, if we model the urban environment as an ensemble of vertical and horizontal surfaces, we can assume that the shapes related to the horizontal surfaces (i.e. the top of the buildings) do not suffer any relevant spatial distortion if detected from two angles of view, while vertical surfaces present strong changes in shape. Starting from this assumption, once each shape in each angular images has been spatially characterized, it is possible to identify univocally the same horizontal surface (i.e. the roof of a building) in each angular image. Finally, the knowledge of the acquisition angles permits the retrieval of the buildings height using simple trigonometric calculations. In this paper the proposed approach has been successfully applied to a WorldView-2 (WV2) very high resolution dataset composed by 5 angular images.

show abstract

Section: Thinningsupporting

confidence: 62%

Section: Thinningmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Retrieval of the Height of Buildings From WorldView-2 Multi-Angular Imagery Using Attribute Filters and Geometric Invariant Moments

Licciardi

Villa

Mura

et al. 2012

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

View full text Add to dashboard Cite

show abstract

“…Considering that a surface texture does not significantly change when shadowed, neighboring nonshadowed segments are usually used to compensate shadowed ones. In the literatures, algorithms include gamma correction method (Massalabi, 2004), linearcorrelation method (Sarabandi, 2004), posteriori probabilities method (Suzuki, 2000), histogram matching method (Tsai, 2003) and theoretical model of removing (Guo, 2006). Almost all these approach are operated band by band in RGB color space, which makes the composite color unnatural (Su, 2006).…”

Section: Introductionmentioning

confidence: 99%

Shadow Segmentation and Compensation in High Resolution Satellite Images

Qin

Xinyi

2008

IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium

View full text Add to dashboard Cite

In high spatial resolution satellite images, shadows are usually cast by elevated objects such as buildings, bridges, and towers, especially in urban region. Shadows may cause loss of feature information, false color tone and shape distortion of objects, which seriously affect the quality of images. Hence, it is important to segment shadow regions and restore their information for image interpretation. This paper presents an effective and robust approach for shadow segmentation and compensation in color satellite images with high spatial resolution. The approach uses normalized saturation-value difference index (NSVDI) in HueSaturation-Value (HSV) color space to detect shadows and exploits histogram matching to recover the information under shadows. Experimental results by applying the proposed approach in the IKONOS color images of urban area demonstrate the effectiveness and feasibility of the proposed approach.

show abstract

“…Therefore, it is only suitable for the measurement over a small area. 2) Shadow analysis (Massalabi et al, 2004;Dare, 2005;Bai and He, 2011). This method uses the lengths of building shadows on satellite image to retrieve the building heights.…”

Section: Study Areamentioning

confidence: 99%

Evaluation of three-dimensional urban expansion: A case study of Yangzhou City, Jiangsu Province, China

et al. 2014

View full text Add to dashboard Cite

Abstract:With rapid urban development in China in the last two decades, the three-dimensional (3D) characteristic has been the main feature of urban morphology. However, the vast majority of researches of urban growth have focused on the planar area (two-dimensional (2D)) expansion. Few studies have been conducted from a 3D perspective. In this paper, the 3D urban expansion of the Yangzhou City, Jiangsu Province, China from 2003 to 2012 was evaluated based on Geographical Information System (GIS) tools and high-resolution remote sensing images. Four indices, namely weighted average height of buildings, volume of buildings, 3D expansion intensity and 3D fractal dimension are used to quantify the 3D urban expansion. The weighted average height of buildings and the volume of buildings are used to illustrate the temporal change of the 3D urban morphology, while the other two indices are used to calculate the expansion intensity and the fractal dimension of the 3D urban morphology. The results show that the spatial distribution of the high-rise buildings in Yangzhou has significantly spread and the utilization of the 3D space of Yangzhou has become more efficient and intensive. The methods proposed in this paper laid a foundation for a wide range of study of 3D urban morphology changes.

show abstract

Detecting information under and from shadow in panchromatic Ikonos images of the city of Sherbrooke

Cited by 15 publications

References 1 publication

Retrieval of the Height of Buildings From WorldView-2 Multi-Angular Imagery Using Attribute Filters and Geometric Invariant Moments

Retrieval of the Height of Buildings From WorldView-2 Multi-Angular Imagery Using Attribute Filters and Geometric Invariant Moments

Shadow Segmentation and Compensation in High Resolution Satellite Images

Evaluation of three-dimensional urban expansion: A case study of Yangzhou City, Jiangsu Province, China

Contact Info

Product

Resources

About