Chunming Han

Web-based visualization of large 3D urban building models

Adaptive rendering of large urban building models has become an important research issue in three-dimensional (3D) geographic information system (GIS) applications. This study explores a way for rendering web-based 3D urban building models. A client–server hybrid rendering approach is presented for large 3D city models, stored on a remote server through a network. The approach combines an efficient multi-hierarchical building representation with a novel image-based method, 3D image impostor generated on demand by a remote server. This approach allows transferring complex scenes progressively while keeping high visualization quality. We also evaluated the rendering and data transferring performance of the proposed approach.

Improved Goldstein SAR Interferogram Filter Based on Adaptive-Neighborhood Technique

The Goldstein filter is one of the most commonly used filters for synthetic aperture radar (SAR) interferograms. The level of noise after filtering is controlled by a filter parameter, “alpha,” the value of which is determined by pixels within the moving window. However, when there exist different features within a single filter window, especially along the border, the value of alpha as estimated from the pixels within the window can be inaccurate and this may result in blurred borders in filtered interferograms. This letter proposes a modified Goldstein filter based on the adaptive-neighborhood technique. The idea of this method is to filter each pixel of the interferogram within an adjusted filter patch. In this adjusted patch, the adaptive-neighborhood pixels retain the original phase values while the “background” pixels are replaced by the mean value of adaptive-neighborhood pixels. Then, the Fourier transform of the complex phase is applied to this adjusted filter patch. The difficulty of estimating the noise level near the borders of different features can be decreased using this new filtering method. The quantitative results from real data show that this newly developed method could reduce the phase noise efficiently while also outperforming the Goldstein, Baran and empirical mode decomposition (EMD) filters by preserving the edges in interferograms.

Efficient occlusion-free visualization for navigation in mountainous areas

In three-dimensional (3D) navigation, if mountainous terrain is displayed based on ordinary perspective projection, viewers often find that the features of interest are occluded, which prevents an overview of the features. This paper presents an approach for the automatic generation of consecutive non-perspective views of mountainous terrain. The proposed method can generate views without occlusions of important features, and allows viewers to navigate the landscape. The ray-tracing technique is employed to detect occlusions. The local elevations that occlude important features are transformed, while the resemblance and realism of the 3D landscape are maintained by solving global optimization problems. The approach maximizes the visibility of the features of interest on the deformed terrain. It also maintains a good balance between the elimination of occlusion and the preservation of resemblance. The occlusion-free visualization framework satisfies the demand for navigation and tour guidance in mountainous areas at interactive frame rates.

Improving the Geolocation Algorithm for Sensors Onboard the ISS: Effect of Drift Angle

Abstract: The drift angle caused by the Earth’s self-rotation may introduce rotational displacement artifact on the geolocation results of imagery acquired by an Earth observing sensor onboard the International Space Station (ISS). If uncorrected, it would cause a gradual degradation of positional accuracy from the center towards the edges of an image. One correction method to account for the drift angle effect was developed. The drift angle was calculated from the ISS state vectors and positional information of the ground nadir point of the imagery. Tests with images acquired by the International Space Station Agriculture Camera (ISSAC) using Google Earth TM as a reference indicated that applying the drift angle correction can reduce the residual geolocation error for the corner points of the ISSAC images from over 1000 to less than 500 m. The improved geolocation accuracy is well within the inherent geolocation uncertainty of up to 800 m, mainly due to imprecise knowledge of the ISS attitude and state parameters required to perform the geolocation algorithm.

Filtering SAR interferometric phase noise using a split-window model

ABSTRACT For interferometric synthetic aperture radar (InSAR) processing, the features of interferometric phase obtained in different coherence regions usually differ from each other. This is called region effect and exists in InSAR coherence map. When coherence value is used as a parameter to filter the phase noise, the result will be highly affected by this region effect. In this paper, we propose a new method of filtering InSAR phase noise using a split-window model. The idea of this method is to incorporate several filters into the model. Different filters will be used when dealing with phase noise locates in different coherence regions. The over-filtering or under-filtering caused by the coherence region effect can be eliminated in this method. As an example to demonstrate the superiority of this method, we incorporated an improved Goldstein filter and empirical mode decomposition filter into the current model. They were included to control phase noise level in the low- and high-coherence regions, respectively. The quantitative results obtained using a COnstellation of small Satellites for the Mediterranean basin Observation (COSMO-SkyMed) image pair over Kilauea volcano in Hawaiian demonstrate the advantages of the newly developed split-window model in filtering different types of noise.

SAR interferometric phase filtering technique based on bivariate empirical mode decomposition

The empirical mode decomposition (EMD) has been widely applied in filtering synthetic aperture radar interferograms. A noisy interferogram can be adaptively decomposed into different frequency modes by EMD. Then, the noise can be eliminated based on the partial reconstruction of relevant modes. However, most fine detail and noise of an interferogram often locate in the same mode, which will lead to an inaccurate estimation of noise level in a local region. In this paper, we proposed an improved filtering method based on bivariate EMD. The idea of our method is to decompose both the phase image and pseudo-coherence map of an interferogram using EMD. The filter level of an interferogram is then controlled by the parameters calculated from the bivariate EMD components. The quantitative results from both simulated and real data show that the bivariate EMD filtering method outperforms the original univariate EMD-based methods. It could achieve a balance between suppressing noise and preserving fine detail of an interferogram.

Research on SAR data integrated processing methodology oriented on earth environment factor inversions

ABSTRACT As an important advanced technique in the field of Earth observations, Synthetic Aperture Radar (SAR) plays a key role in the study of global environmental change, resources exploration, disaster mitigation, urban environments, and even lunar exploration. However, studies on imaging, image processing, and Earth factor inversions have often been conducted independently for a long time, which significantly limits the application effectiveness of SAR remote sensing due to the lack of an overall integrated design scheme and integrated information processing. Focusing on this SAR application issue, this paper proposes and describes a new SAR data processing methodology – SAR data integrated processing (DIP) oriented on Earth environment factor inversions. The simple definition, typical integrated modes and overall implementation ideas are introduced. Finally, focusing on building information extraction (man-made targets) and sea ice classification (natural targets) applications, three SAR DIP methods and experiments are conducted. Improved results are obtained under the guidance of the SAR DIP framework. Therefore, the SAR DIP theoretical framework and methodology represent a new SAR science application mode that has the capability to improve the SAR remote sensing quantitative application level and promote the development of new theories and methodologies.

Joint shape and color descriptors for 3D urban model retrieval

ABSTRACT With the rapid development of photogrammetry, computer vision and three-dimensional (3D) modeling technologies, it is possible to efficiently construct detailed 3D urban models. Accordingly, large corpora of 3D models, such as the Google 3D Warehouse, are now becoming freely available on the web. How to find the proper 3D urban models is a challenging research issue. In this paper, we join shape descriptors and color descriptors for 3D urban model retrieval. The query objects are localized and segmented automatically from the input images by using a new selective search voting algorithm. Through combining the normalization with the light field descriptor, the Horizontal Light Descriptor is introduced to measure the shape similarity among the normalized urban models. The color descriptors are used to represent the color information of the urban models. The two types of descriptors are joined to search 3D urban models similar to the query objects. Experimental results have shown the effectiveness of our approach.

Study on the estimation of the range parameter for SAR signal processing

Range is the key parameter for synthetic aperture radar imaging. The range parameter estimation using the relationship between the radar internal calibration signals and system signal is studied in this paper. The delay of the system signal is computed based on the delays of the three internal calibration signals recorded. Using the approach proposed, the standard deviation of the range delay of the radar system signal is about 0.1mm.

Block adjustment of airborne InSAR based on interferogram phase and POS data

High-precision surface elevation information in large scale can be obtained efficiently by airborne Interferomatric Synthetic Aperture Radar (InSAR) system, which is recently becoming an important tool to acquire remote sensing data and perform mapping applications in the area where surveying and mapping is difficult to be accomplished by spaceborne satellite or field working. . Based on the study of the three-dimensional (3D) positioning model using interferogram phase and Position and Orientation System (POS) data and block adjustment error model, a block adjustment method to produce seamless wide-area mosaic product generated from airborne InSAR data is proposed in this paper. The effect of 6 parameters, including trajectory and attitude of the aircraft, baseline length and incline angle, slant range, and interferometric phase, on the 3D positioning accuracy is quantitatively analyzed. Using the data acquired in the field campaign conducted in Mianyang county Sichuan province, China in June 2011, a mosaic seamless Digital Elevation Model (DEM) product was generated from 76 images in 4 flight strips by the proposed block adjustment model. The residuals of ground control points (GCPs), the absolute positioning accuracy of check points (CPs) and the relative positioning accuracy of tie points (TPs) both in same and adjacent strips were assessed. The experimental results suggest that the DEM and Digital Orthophoto Map (DOM) product generated by the airborne InSAR data with sparse GCPs can meet mapping accuracy requirement at scale of 1:10 000.