Microwave Radiometry Imaging for Forest Fire Detection: A Simulation Study

Bonafoni, Stefania; Alimenti, F.; Angelucci, G.; Tasselli, G.

doi:10.2528/pier10111901

Cited by 19 publications

(11 citation statements)

References 12 publications

(23 reference statements)

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“…PMMW has been widely used in earth remote sensing, radio astronomy, cosmology, air sounding, and commercial applications [1]. For instance, during the imaging of earth remote sensing, PMMW imaging system can pass through the cloud layer and dust to achieve the image of the ground; during the forest fire detection it is also capable to detect the fire source which is optically masked by obstacles [2]. Synthetic aperture imaging radiometer (SAIR), which employs a number of identical antennas and receivers distributed in space to form sparse array, can attain desirable spatial resolutions without scanning system [3].…”

Section: Introductionmentioning

confidence: 99%

Passive Millimeter Wave Image Denoising Based on Adaptive Manifolds

Zhu¹,

Li²,

Chen³

et al. 2014

PIER B

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Abstract-Since the characters of poor inherent resolution and low signal-to-noise limit the application of the passive millimeter wave (PMMW) image, it is particularly important to improve the resolution and denoise the PMMW image. In this paper, the adaptive manifolds filtering algorithm based on non-local means (AM-NLM) is illustrated in detail. And an improved version of AM-NLM filtering algorithm is proposed for processing the PMMW image. The proposed algorithm firstly applies the AM-NLM filtering to obtain the basic denoised PMMW image. Then the image enhancement based on Laplacian of Gaussian operator is performed to enhance the edge of the target in PMMW image. Finally, the hard-threshold filtering with different thresholds is adopted to filter each dimension to achieve the final filtering response. Experimental results have shown that the proposed PMMW filtering algorithm has better and more satisfactory performance compared to AM-NLM, both in subjective visual effect and objective image quality metric. Additionally, our proposed algorithm is also available for real PMMW images.

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Section: Introductionmentioning

confidence: 99%

Passive Millimeter Wave Image Denoising Based on Adaptive Manifolds

Zhu¹,

Li²,

Chen³

et al. 2014

PIER B

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“…In recent years, MIT has also been a great success in two phase flow monitoring which involves gas/melting metal flow for metal casting applications, based on the high conductivity contrast between melted metal and gas [4,5]. Several low and high frequency electromagnetic imaging techniques similar to MIT may provide great monitoring and control opportunities in the field of industrial process tomography [29][30][31][32][33][34].…”

Section: Introductionmentioning

confidence: 99%

Two-Phase Low Conductivity Flow Imaging Using Magnetic Induction Tomography

Wei¹,

Soleimani²

2012

PIER

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Abstract-Magnetic Induction Tomography (MIT) is a new and emerging type of tomography technique that is able to map the distribution of all three passive electromagnetic properties, however most of the current interests are focusing on the conductivity and permeability imaging. In an MIT system, coils are used as separate transmitters or sensors, which can generate the background magnetic field and detect the perturbed magnetic field respectively. Through switching technique the same coil can work as transceiver which can generate field at a time and detect the field at another time. Because magnetic field can easily penetrate through the non-conductive barrier, the sensors do not need direct contact with the imaging object. These non-invasive and contactless features make it an attractive technique for many applications compared to the traditional contact electrode based electrical impedance tomography. Recently, MIT has become a promising monitoring technique in industrial process tomography, for example MIT has been used to determine the distribution of liquidised metal and gas (high conductivity two phase flow monitoring) for metal casting applications. In this paper, a low conductivity two phase flow MIT imaging is proposed so the reconstruction of the low contrast samples (< 6 S/m) can be realised, e.g., gas/ionised liquid. An MIT system is developed to test the feasibility. The system utilises 16 coils (8 transmitters and 8 receivers) and an operating frequency of 13 MHz. Three different experiments were conducted to evaluate all possible situations of two phase flow imaging: 1) conducting objects inside a non-conducting background, 2) conducting objects inside a conducting background (low contrast) and 3) non-conducting objects inside a conducting background. Images are reconstructed using the linearised inverse method with regularisation. An experiment was designed to image the non-conductive samples inside a conducting

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“…Microwave radiometers are powerful sensors for high-resolution observations of the Earth at relatively low frequencies [1,2]. The low microwave frequency range offers high penetration ability through clouds and into the top layer of the Earth surface.…”

Section: Introductionmentioning

confidence: 99%

A Compressive Sensing Approach for Synthetic Aperture Imaging Radiometers

Li¹,

Zhou²,

Ren³

et al. 2013

PIER

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Abstract-The aperture synthesis technology represents a promising new approach to microwave radiometers for high-resolution observations of the Earth from geostationary orbit. However, the future application of the new technology may be limited by its large number of antennas, receivers, and correlators. In order to reduce significantly the complexity of the on-board hardware requirements, a novel method based on the recently developed theory of compressive sensing (CS) is proposed in this paper. Due to the fact that the brightness temperature distributions of the Earth have a sparse representation in some proper transform domain -for example, in terms of spatial finite-differences or their wavelet coefficients, we use the CS approach to significantly undersample the visibility function. Thus the number of antennas, receivers, and correlators can be further reduced than those based on the traditional methods that obey the Shannon/Nyquist sampling theorem. The reconstruction is performed by minimizing the 1 norm of a transformed image. The effectiveness of the proposed approach is validated by numerical simulations using the image corresponding to AMSU-A over the Pacific.

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Microwave Radiometry Imaging for Forest Fire Detection: A Simulation Study

Cited by 19 publications

References 12 publications

Passive Millimeter Wave Image Denoising Based on Adaptive Manifolds

Passive Millimeter Wave Image Denoising Based on Adaptive Manifolds

Two-Phase Low Conductivity Flow Imaging Using Magnetic Induction Tomography

A Compressive Sensing Approach for Synthetic Aperture Imaging Radiometers

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