Papers by Vassilis Tsagaris
Space Optics 1994: Earth Observation and Astronomy, 1994
MERIS is a passive optical instrument, that will fly on the First Polar Orbiting Earth observatio... more MERIS is a passive optical instrument, that will fly on the First Polar Orbiting Earth observation mission ENVISAT 1, scheduled for launch mid 1998. The study and development of this instrument is currently carried by an international team led by AEROSPATIALE. The instrument primary mission goal is to monitor bio-optical ocean parameters on a large scale. Secondary goals of MERIS include atmospheric investigation on cloud and aerosols parameters and on land surface processes. The instrument will perform 15 spectral images, programmable in width and position with a spectral sampling interval of 1.25 nm within the visible spectral range of 400 nm to 1050 nm. MERIS images will have a swath width of 1100 km and spatial resolution of 300 m.
2016 IEEE International Smart Cities Conference (ISC2), 2016
A survey of the herpetofauna of Yarrigan National Park (NP), in the southern Pilliga forest in no... more A survey of the herpetofauna of Yarrigan National Park (NP), in the southern Pilliga forest in northern inland New South Wales, was done over the period 2011 to 2013. The total identified herpetofauna community comprised 11 frog species (three families) and 35 reptiles (10 families) and includes a mix of eastern (Bassian), western (Eyrean) and northern (Torresian) species. This study demonstrates the significant species diversity, biogeographical interest and conservation value of the Pilliga forest's herpetofauna. Noteworthy findings from this study included a number of declining woodland reptile species (Nobbi Diporiphora nobbi, Australian Coral Snake Brachyurophis australis and Inland Carpet Python Morelia spilota metcalfei), locally rare species (Excitable Delma Delma tincta and Southern Rainbow Skink Carlia tetradactyla) and edge of range species (Litter Skink Lygisaurus foliorum). The study provides a useful benchmark of the composition and status of the herpetofauna community of Yarrigan NP in the first decade following a land management shift from timber production to conservation.
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2015
Data fusion has lately received a lot of attention as an effective technique for several target d... more Data fusion has lately received a lot of attention as an effective technique for several target detection and classification applications in different remote sensing areas. In this work, a novel data fusion scheme for improving the detection accuracy of ship targets in polarimetric data is proposed, based on 2D principal components analysis (2D-PCA) technique. By constructing a fused image from different polarization channels, increased performance of ship target detection is achieved having higher true positive and lower false positive detection accuracy as compared to single channel detection performance. In addition, the use of 2D-PCA provides the ability to discriminate and classify objects and regions in the resulting image representation more effectively, with the additional advantage of being more computational efficient and requiring less time to determine the corresponding eigenvectors, compared to e.g. conventional PCA. Throughout our analysis, a constant false alarm rate (CFAR) detection model is applied to characterize the background clutter and discriminate ship targets based on the Weibull distribution and the calculation of local statistical moments for estimating the order statistics of the background clutter. Appropriate pre-processing and post-processing techniques are also introduced to the process chain, in order to boost ship discrimination and suppress false alarms caused by range focusing artifacts. Experimental results provided on a set of Envisat and RadarSat-2 images (dual and quad polarized respectively), demonstrate the advantage of the proposed data fusion scheme in terms of detection accuracy as opposed to single data ship detection and conventional PCA, in various sea conditions and resolutions. Further investigation of other data fusion techniques is currently in progress.
Energy Optimization and Scavenging Techniques, 2012
Image and Signal Processing for Remote Sensing XIII, 2007
blessing. For the remainder, doctors should consider the herd immunity that evidently accrues in ... more blessing. For the remainder, doctors should consider the herd immunity that evidently accrues in homes with high immunisation rates2' and then wrestle with their consciences.
2011 2nd International Conference on Space Technology, 2011
... Experimental results, provided on two hyperspectral dataset acquired by CHRIS sensor and the ... more ... Experimental results, provided on two hyperspectral dataset acquired by CHRIS sensor and the AVIRIS instrument, demonstrate the advantage of the proposed work. ... In order to provide the results of 2D-PCA fusion for the CHRIS dataset, the electromagnetic spectrum Page 4. ...
Optical Engineering, 2009
... The same conclusions about the performance of the four different fusion methods can be derive... more ... The same conclusions about the performance of the four different fusion methods can be derived ... important issues in the color image fusion performance evaluationthat is, the assessment of information ... final image and also the distribution of colors in the final fused color image ...
IEEE Transactions on Geoscience and Remote Sensing, 2012
Image fusion has attracted a lot of interest in recent years. As a result, different fusion metho... more Image fusion has attracted a lot of interest in recent years. As a result, different fusion methods have been proposed mainly in the fields of remote sensing and computer (e.g., night) vision, while hardware implementations have been also presented to tackle real-time processing in different application domains. In this paper, a linear pixel-level fusion method is employed and implemented on a field-programmable-gate-array-based hardware system that is suitable for remotely sensed data. Our work incorporates a fusion technique (called VTVA) that is a linear transformation based on the Cholesky decomposition of the covariance matrix of the source data. The circuit is composed of different modules, including covariance estimation, Cholesky decomposition, and transformation ones. The resulted compact hardware design can be characterized as a linear configurable implementation since the color properties of the final fused color can be selected by the user in a way of controlling the resulting correlation between color components.
Engineering Against Fracture
... power is kept at low levels limiting interference problems and lowering overall energy consum... more ... power is kept at low levels limiting interference problems and lowering overall energy consumption ... is to make it easier for different manufacturers to develop smart sensors ... 7. BV Dasarathy, Sensor Fusion Potential Exploitation-Innovative Architectures and Illustrative Applications ...
Envisat Ers Symposium, Apr 1, 2005
In this paper the problem of enhanced colour representation of MERIS data is discussed. Four meth... more In this paper the problem of enhanced colour representation of MERIS data is discussed. Four methods are presented which tackle the problem of multispectral data colour visualisation. In order to assess these colour display strategies a data analysis using both statistical and information measures is presented. The performance of the proposed methods is evaluated objectively by means of mutual information.
The Kullback-Leibler (KL) divergence, a fundamental concept in information theory used to quantif... more The Kullback-Leibler (KL) divergence, a fundamental concept in information theory used to quantify probability density differences, is herein employed in assessing the color content of digital images. For this purpose digital images are encoded in the CIELAB color space and modeled as discrete random fields, which are assumed to be described sufficiently by three-dimensional probability density functions. Subsequently, using the KL divergence, a global quality assessment of an image is presented as the information content of the CIELAB encoding of the image relative to channel capacity. This is expressed by an image with "maximum realizable color information (MRCI)" defined in this paper. Additionally, one-dimensional estimates of the marginal distributions in luminance, chroma, and hue are explored, and the proposed quality assessment is examined relative to KL divergences based on these distributions. The proposed measure is tested using color images, pseudocolor representations and different renderings of the same scene.
Journal of Electronic Imaging, 2005
Detection of edges in multispectral images has been a challenging task in the research community ... more Detection of edges in multispectral images has been a challenging task in the research community over the past few years. In this work, a novel vector-based approach is adopted for edge detection in multichannel remotely sensed images. The discontinuity between homogeneous regions in the image is detected using the image density value estimated at the mean vector of the sliding window. The proposed algorithm is nonparametric, computationally simple to implement, providing us with dimensionality reduction in the multivariate feature space.
ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2015
ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2015
SAR based ship detection and classification are important elements of maritime monitoring applica... more SAR based ship detection and classification are important elements of maritime monitoring applications. Recently, high-resolution SAR data have opened new possibilities to researchers for achieving improved classification results. In this work, a hierarchical vessel classification procedure is presented based on a robust feature extraction and selection scheme that utilizes scale, shape and texture features in a hierarchical way. Initially, different types of feature extraction algorithms are implemented in order to form the utilized feature pool, able to represent the structure, material, orientation and other vessel type characteristics. A two-stage hierarchical feature selection algorithm is utilized next in order to be able to discriminate effectively civilian vessels into three distinct types, in COSMO-SkyMed SAR images: cargos, small ships and tankers. In our analysis, scale and shape features are utilized in order to discriminate smaller types of vessels present in the available SAR data, or shape specific vessels. Then, the most informative texture and intensity features are incorporated in order to be able to better distinguish the civilian types with high accuracy. A feature selection procedure that utilizes heuristic measures based on features’ statistical characteristics, followed by an exhaustive research with feature sets formed by the most qualified features is carried out, in order to discriminate the most appropriate combination of features for the final classification. In our analysis, five COSMO-SkyMed SAR data with 2.2m x 2.2m resolution were used to analyse the detailed characteristics of these types of ships. A total of 111 ships with available AIS data were used in the classification process. The experimental results show that this method has good performance in ship classification, withan overall accuracy reaching 83%. Further investigation of additional features and proper feature selection is currently in progress.
2002 14th International Conference on Digital Signal Processing Proceedings. DSP 2002 (Cat. No.02TH8628), 2002
ABSTRACT
Energy Optimization and Scavenging Techniques, 2012
SPIE Newsroom, 2008
Synthetic aperture radar (SAR) systems are active sensors offer-ing unique high spatial resolutio... more Synthetic aperture radar (SAR) systems are active sensors offer-ing unique high spatial resolution regardless of weather or other conditions, with wide area coverage over swaths up to 500km across. Furthermore, SAR data can be acquired with great reli-ability to enable precision ...
Progress In Electromagnetics Research, 2007
Abstract: This paper presents a combined Entropy Decomposition and Support Vector Machine (EDSVM)... more Abstract: This paper presents a combined Entropy Decomposition and Support Vector Machine (EDSVM) technique for Synthetic Aperture Radar (SAR) image classification with the application on rice monitoring. The objective of this paper is to assess the use of multi-temporal data for the supervised classification of rice planting area based on different schedules. Since adequate priori information is needed for this supervised classification, ground truth measurements of rice fields were conducted at Sungai Burung, Selangor, ...
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Papers by Vassilis Tsagaris