Extraction of tidal channel networks from airborne scanning laser altimetry and aerial photography

The study of the morphodynamics of tidal channel networks is important because of their role in tidal propagation and the evolution of salt-marshes and tidal flats. Channel dimensions range from tens of metres wide and metres deep near the low water mark to only 20-30cm wide and 20cm deep for the smallest channels on the marshes. The conventional method of measuring the networks is cumbersome, involving manual digitising of aerial photographs. This paper describes a semi-automatic knowledge-based network extraction method that is being implemented to work using airborne scanning laser altimetry (and later aerial photography). The channels exhibit a width variation of several orders of magnitude, making an approach based on multi-scale line detection difficult. The processing therefore uses multi-scale edge detection to detect channel edges, then associates adjacent anti-parallel edges together to form channels using a distance-with-destination transform. Breaks in the networks are repaired by extending channel ends in the direction of their ends to join with nearby channels, using domain knowledge that flow paths should proceed downhill and that any network fragment should be joined to a nearby fragment so as to connect eventually to the open sea.

Uses of airborne scanning laser altimetry for river flood modelling and coastal geomorphology

Two ongoing projects at ESSC that involve the development of new techniques for extracting information from airborne LiDAR data and combining this information with environmental models will be discussed. The first project in conjunction with Bristol University is aiming to improve 2-D river flood flow models by using remote sensing to provide distributed data for model calibration and validation. Airborne LiDAR can provide such models with a dense and accurate floodplain topography together with vegetation heights for parameterisation of model friction. The vegetation height data can be used to specify a friction factor at each node of a model’s finite element mesh. A LiDAR range image segmenter has been developed which converts a LiDAR image into separate raster maps of surface topography and vegetation height for use in the model. Satellite and airborne SAR data have been used to measure flood extent remotely in order to validate the modelled flood extent. Methods have also been developed for improving the models by decomposing the model’s finite element mesh to reflect floodplain features such as hedges and trees having different frictional properties to their surroundings. Originally developed for rural floodplains, the segmenter is currently being extended to provide DEMs and friction parameter maps for urban floods, by fusing the LiDAR data with digital map data. The second project is concerned with the extraction of tidal channel networks from LiDAR. These networks are important features of the inter-tidal zone, and play a key role in tidal propagation and in the evolution of salt-marshes and tidal flats. The study of their morphology is currently an active area of research, and a number of theories related to networks have been developed which require validation using dense and extensive observations of network forms and cross-sections. The conventional method of measuring networks is cumbersome and subjective, involving manual digitisation of aerial photographs in conjunction with field measurement of channel depths and widths for selected parts of the network. A semi-automatic technique has been developed to extract networks from LiDAR data of the inter-tidal zone. A multi-level knowledge-based approach has been implemented, whereby low level algorithms first extract channel fragments based mainly on image properties then a high level processing stage improves the network using domain knowledge. The approach adopted at low level uses multi-scale edge detection to detect channel edges, then associates adjacent anti-parallel edges together to form channels. The higher level processing includes a channel repair mechanism.

Detection and thinning of edges in previously known directions

This work presents a study on the generation of digital masks aiming at edge detection with previously known directions. This solution is important when edge direction is available either from a direction histogram or from a prediction based on camera and object models. A modification in the non-maximum suppression method of thinning is also presented enabling the comparison of local maxima for any edge directions. Results with a synthetic image and with crops of a CBERS satellite images are presented showing an example with its application in road detection, provided that directions are previously known.

Dynamic programming approach for road centerline extraction from digital images

This paper presents a dynamic programming approach for semi-automated road extraction from medium-and high-resolution images. This method is a modified version of a pre-existing dynamic programming method for road extraction from low-resolution images. The basic assumption of this pre-existing method is that roads manifest as lines in low-resolution images (pixel footprint> 2 m) and as such can be modeled and extracted as linear features. On the other hand, roads manifest as ribbon features in medium- and high-resolution images (pixel footprint ≤ 2 m) and, as a result, the focus of road extraction becomes the road centerlines. The original method can not accurately extract road centerlines from medium- and high- resolution images. In view of this, we propose a modification of the merit function of the original approach, which is carried out by a constraint function embedding road edge properties. Experimental results demonstrated the modified algorithm's potential in extracting road centerlines from medium- and high-resolution images.

Border detection in digital images: An approach by fuzzy numbers

The purpose of this paper is to introduce a new approach for edge detection in gray shaded images. The proposed approach is based on the fuzzy number theory. The idea is to deal with the uncertainties concerning the gray shades making up the image, and thus calculate the appropriateness of the pixels in relation to an homogeneous region around them. The pixels not belonging to the region are then classified as border pixels. The results have shown that the technique is simple, computationally efficient and with good results when compared with both the traditional border detectors and the fuzzy edge detectors. © 2007 IEEE.

Algoritmos de detecção de bordas implementados em FPGA

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Extração semi-automática de edificações com análise do modelo numérico de elevações

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Implementação em FPGA de um sistema para processamento de imagens digitais para aplicações diversificadas

Pós-graduação em Ciência da Computação - IBILCE

Medidas de deslocamento e vibrações através de imagens de câmeras digitais

Pós-graduação em Engenharia Mecânica - FEIS

Segmentação de texturas em imagens digitais utilizando wavelets redundantes

Pós-graduação em Matematica Aplicada e Computacional - FCT

Tecniche per la separazione live di piani di profondita in un flusso video mediante Kinect e una applicazione nell'intrattenimento digitale

Keying e composizione sono da sempre tecniche ampiamente utilizzate in contesti multimediali, quali produzione cinematografica e televisiva; il chroma keying è in particolare la tecnica più popolare, ma presenta una serie di limiti e problematiche. In questo elaborato viene proposta una tecnica alternativa di estrazione, basata sull'uso della profondità, operante in tempo reale e che sfrutta il device Kinect di Microsoft. Sono proposti una serie di algoritmi, basati su tecniche di edge detection, utilizzati per il miglioramento della depth map lungo i bordi di estrazione; viene infine testato il risultato ottenuto dall'implementazione del sistema e proposta una possibile applicazione nell'ambito del teatro multimediale.

A new information fusion method for land-use classification using high resolution satellite imagery

Satellite image classification involves designing and developing efficient image classifiers. With satellite image data and image analysis methods multiplying rapidly, selecting the right mix of data sources and data analysis approaches has become critical to the generation of quality land-use maps. In this study, a new postprocessing information fusion algorithm for the extraction and representation of land-use information based on high-resolution satellite imagery is presented. This approach can produce land-use maps with sharp interregional boundaries and homogeneous regions. The proposed approach is conducted in five steps. First, a GIS layer - ATKIS data - was used to generate two coarse homogeneous regions, i.e. urban and rural areas. Second, a thematic (class) map was generated by use of a hybrid spectral classifier combining Gaussian Maximum Likelihood algorithm (GML) and ISODATA classifier. Third, a probabilistic relaxation algorithm was performed on the thematic map, resulting in a smoothed thematic map. Fourth, edge detection and edge thinning techniques were used to generate a contour map with pixel-width interclass boundaries. Fifth, the contour map was superimposed on the thematic map by use of a region-growing algorithm with the contour map and the smoothed thematic map as two constraints. For the operation of the proposed method, a software package is developed using programming language C. This software package comprises the GML algorithm, a probabilistic relaxation algorithm, TBL edge detector, an edge thresholding algorithm, a fast parallel thinning algorithm, and a region-growing information fusion algorithm. The county of Landau of the State Rheinland-Pfalz, Germany was selected as a test site. The high-resolution IRS-1C imagery was used as the principal input data.

Neuregulin-1 beta attenuates doxorubicin-induced alterations of excitation-contraction coupling and reduces oxidative stress in adult rat cardiomyocytes

Treatment of metastatic breast cancer with doxorubicin (Doxo) in combination with trastuzumab, an antibody targeting the ErbB2 receptor, results in an increased incidence of heart failure. Doxo therapy induces reactive oxygen species (ROS) and alterations of calcium homeostasis. Therefore, we hypothesized that neuregulin-1 beta (NRG), a ligand of the cardiac ErbB receptors, reduces Doxo-induced alterations of EC coupling by triggering antioxidant mechanisms. Adult rat ventricular cardiomyocytes (ARVM) were isolated and treated for 18-48 h. SERCA protein was analyzed by Western blot, EC coupling parameters by fura-2 and video edge detection, gene expression by RT-PCR, and ROS by DCF-fluorescence microscopy. At clinically relevant doses Doxo reduced cardiomyocytes contractility, SERCA protein and SR calcium content. NRG, similarly as the antioxidant N-acetylcystein (NAC), did not affect EC coupling alone, but protected against Doxo-induced damage. NRG and Doxo showed an opposite modulation of glutathione reductase gene expression. NRG, similarly as NAC, reduced peroxide- or Doxo-induced oxidative stress. Specific inhibitors showed, that the antioxidant action of NRG depended on signaling via the ErbB2 receptor and on the Akt- and not on the MAPK-pathway. Therefore, NRG attenuates Doxo-induced alterations of EC coupling and reduces oxidative stress in ARVM. Inhibition of the ErbB2/NRG signaling pathway by trastuzumab in patients concomitantly treated with Doxo might prevent beneficial effects of NRG in the myocardium.

Brain responses to auditory and visual stimulus offset: Shared representations of temporal edges

Edges are crucial for the formation of coherent objects from sequential sensory inputs within a single modality. Moreover, temporally coincident boundaries of perceptual objects across different sensory modalities facilitate crossmodal integration. Here, we used functional magnetic resonance imaging in order to examine the neural basis of temporal edge detection across modalities. Onsets of sensory inputs are not only related to the detection of an edge but also to the processing of novel sensory inputs. Thus, we used transitions from input to rest (offsets) as convenient stimuli for studying the neural underpinnings of visual and acoustic edge detection per se. We found, besides modality-specific patterns, shared visual and auditory offset-related activity in the superior temporal sulcus and insula of the right hemisphere. Our data suggest that right hemispheric regions known to be involved in multisensory processing are crucial for detection of edges in the temporal domain across both visual and auditory modalities. This operation is likely to facilitate cross-modal object feature binding based on temporal coincidence. Hum Brain Mapp, 2008. (c) 2008 Wiley-Liss, Inc.

Inhibition of ErbB2/neuregulin signaling augments paclitaxel-induced cardiotoxicity in adult ventricular myocytes

Paclitaxel (Taxol) has been successfully combined with the monoclonal antibody trastuzumab (Herceptin) in the treatment of ErbB2 overexpressing cancers. However, this combination therapy showed an unexpected synergistic increase in cardiac dysfunction. We have studied the mechanisms of paclitaxel/anti-ErbB2 cardiotoxicity in adult rat ventricular myocytes (ARVM). Myofibrillar organization was assessed by immunofluorescence microscopy and cell viability was tested by the TUNEL-, LDH- and MTT-assay. Oxidative stress was measured by DCF-fluorescence and myocyte contractile function by video edge-detection and fura-2 fluorescence. Treatment of ARVM with paclitaxel or antibodies to ErbB2 caused a significant increase in myofilament degradation, similarly as observed with an inhibitor of MAPK-signaling, but not apoptosis, necrosis or changes in mitochondrial activity. Paclitaxel-treatment and anti-ErbB2 reduced Erk1/2 phosphorylation. Paclitaxel increased diastolic calcium, shortened relaxation time and reduced fractional shortening in combination with anti-ErbB2. A minor increase in oxidative stress by paclitaxel or anti-ErbB2 was found. We conclude, that concomitant inhibition of ErbB2 receptors and paclitaxel treatment has an additive worsening effect on adult cardiomyocytes, mainly discernible in changes of myofibrillar structure and function, but in the absence of cell death. A potential mechanism is the modulation of the MAPK/Erk1/2 signaling by both drugs.