Search results for "Computer Vision and Pattern Recognition"
showing 10 items of 997 documents
Estimation of Evapotranspiration by Hargreaves Formula and Remotely Sensed Data in Semi-arid Mediterranean Areas
1997
Abstract A methodology is proposed for estimating evapotranspiration by Hargreaves formula and image analysis of remotely sensed data. At first, for a large sicilian basin (Belice basin), theactualevapotranspiration values are estimated by the energy balance equation, spectral data of two Landsat TM images and ground agrometereological measurements. Then theseactualevapotranspiration estimates and thereferenceevapotranspiration values obtained by a slightly modified Hargreaves formula, which incorporates the outgoing short-wave radiation and an albedo coefficient equal to 0·23, are used for calculating suitable crop coefficients. Finally, the minimum area of each land-use map unit, obtained…
Assessing actual evapotranspiration via surface energy balance aiming to optimize water and energy consumption in large scale pressurized irrigation …
2017
Satellite imagery provides a dependable basis for computational models that aimed to determine actual evapotranspiration (ET) by surface energy balance. Satellite-based models enables quantifying ET over large areas for a wide range of applications, such as monitoring water distribution, managing irrigation and assessing irrigation systems’ performance. With the aim to evaluate the energy and water consumption of a large scale on-turn pressurized irrigation system in the district of Aguas Nuevas, Albacete, Spain, the satellite-based image-processing model SEBAL was used for calculating actual ET. The model has been applied to quantify instantaneous, daily, and seasonal actual ET over high- …
Hypergraph imaging: an overview
2002
Hypergraph theory as originally developed by Berge (Hypergraphe, Dunod, Paris, 1987) is a theory of finite combinatorial sets, modeling lot of problems of operational research and combinatorial optimization. This framework turns out to be very interesting for many other applications, in particular for computer vision. In this paper, we are going to survey the relationship between combinatorial sets and image processing. More precisely, we propose an overview of different applications from image hypergraph models to image analysis. It mainly focuses on the combinatorial representation of an image and shows the effectiveness of this approach to low level image processing; in particular to seg…
Robust H∞ filtering for networked control systems with markovian jumps and packet dropouts
2014
Published version of an article in the journal: Modeling, Identification and Control. Also available from the publisher at: http://dx.doi.org/10.4173/mic.2014.3.3 Open Access This paper deals with the H∞ filtering problem for uncertain networked control systems. In the study, network-induced delays, limited communication capacity due to signal quantization and packet dropout are all taken into consideration. The finite distributed delays with probability of occurrence in a random way is introduced in the network.The packet dropout is described by a Bernoulli process. The system is modeled as Markovian jumps system with partially known transition probabilities. A full-order filter is designe…
Quantitative comparison of new image processing methods for volumetric analysis of left ventricular contrast echocardiograms
2003
An effort has been made to develop image processing methods which allow a definite and precise tracking of the borderline of the ventricle in two-dimensional echocardiograms. Experience is reported with two new methods, which are based on the gray-level rise (GL) and the signal-to-noise ratio (SNR) in combined heart-phase-triggered image series. A quantitative comparison of these time-series methods is presented with respect to the interpretation of a single native image (noncontrast image), a single contrast-material image, the corresponding subtraction image, and the corresponding color superposition image. The comparison is based on the calculation of the ejection fraction using the abov…
The role of perceptual contrast non-linearities in image transform quantization
2000
Abstract The conventional quantizer design based on average error minimization over a training set does not guarantee a good subjective behavior on individual images even if perceptual metrics are used. In this work a novel criterion for transform coder design is analyzed in depth. Its aim is to bound the perceptual distortion in each individual quantization according to a non-linear model of early human vision. A common comparison framework is presented to describe the qualitative behavior of the optimal quantizers under the proposed criterion and the conventional rate-distortion based criterion. Several underlying metrics, with and without perceptual non-linearities, are used with both cr…
Analysis of image formation with a photon scanning tunneling microscope
1996
International audience; The photon scanning tunneling microscope (PSTM) is based on the frustration of a total internal reflected beam by the end of an optical fiber. Until now it has been used to obtain topographic information, generally for smooth samples. We report theoretical as well as experimental results on the observation of a step on a quartz substrate with the PSTM. These results demonstrate the effects on image formation of the distance between the fiber tip and the sample surface, the orientation of the incident beam with respect to the step, the polarization, and the coherence of the light. Good agreement exists between numerical simulations and experiments. We show that a pert…
Multimodal biometric recognition systems using deep learning based on the finger vein and finger knuckle print fusion
2020
Recognition systems using multimodal biometrics attracts attention because they improve recognition efficiency and high-security level compared to the unimodal biometrics system. In this study, the authors present a secure multimodal biometrics recognition system based on the deep learning method that uses convolutional neural networks (CNNs). The authors propose two multimodal architectures using the finger knuckle print (FKP) and the finger vein (FV) biometrics with different levels of fusion: the features level fusion and scores level fusion. The features extraction for FKP and FV are performed using transfer learning CNN architectures: AlexNet, VGG16, and ResNet50. The key step aims to …
Multi-resolution spatial unmixing for MERIS and Landsat image fusion
2016
Nowadays, the increasing quantity of applications using images from Earth Observation satellites makes demanding better spatial, spectral and temporal resolutions. Nevertheless, due to the technical constraint of a trade off between spatial and spectral resolutions, and between spatial resolution and coverage, high spatial resolution is related with low spectral and temporal resolutions and vice versa. Data fusion methods are a good solution to combine information from multiple sensors in order to obtain image products with better characteristics. In this paper, we propose an image fusion approach based on a multi-resolution and multi-source unmixing. The proposed methodology yields a compo…
An interpolation-based data fusion scheme for enhancing the resolution of thermal image sequences
2014
In several human activities, such as agriculture and forest management, the monitoring of radiometric surface temperature is key. In particular both high spatial resolution and high acquisition rate are desirable but, due to the hardware limitations, these two characteristics are not met by the same sensor. The fusion of remotely sensed data acquired by sensors with different spatial and temporal resolution is a profitable choice to face this issue. When the real-time requirement is relaxed, the data sequence can be processed as a whole, allowing to improve the final result. Within this framework, we propose a novel batch sharpening strategy, relying on interpolation, data fusion and Bayesi…