Prof. Mauro Dalla Mura Profile

Prof. Mauro Dalla Mura

at Gipsa-Lab

SPIE Involvement:

Author

Publications (13)

Proceedings Article | 5 October 2023 Paper

Training dataset optimization for deep learning applied to optical proximity correction on non-regular hole masks

Mathis Urard, Clément Paquet, Charlotte Beylier, Jean-Noël Pena, Alice Caplier, Mauro Dalla Mura, Romain Bange, Roberto Guizzetti

Proceedings Volume 12802, 128020A (2023) https://doi.org/10.1117/12.2675612

KEYWORDS: Education and training, Machine learning, Optical proximity correction, Design and modelling, Databases, Photomasks, Source mask optimization, Lithography, Data modeling, Deep learning

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Proceedings Article | 7 October 2019 Presentation + Paper

Gas characterisation based on a snapshot interferometric imaging spectrometer

Aneline Dolet, Daniele Picone, Mauro Dalla Mura, Didier Voisin, Silvère Gousset, Sylvain Douté, Etienne Le Coarer

Proceedings Volume 11155, 1115502 (2019) https://doi.org/10.1117/12.2533338

KEYWORDS: Interferometers, Interferometry, Sensors, Spectroscopy, Fourier transforms, Prototyping, Fabry–Perot interferometry, Calibration, Hyperspectral imaging, Imaging systems

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Proceedings Article | 24 May 2018 Presentation + Paper

Pansharpening of images acquired with color filter arrays

Daniele Picone, Mauro Dalla Mura, Laurent Condat

Proceedings Volume 10677, 106770B (2018) https://doi.org/10.1117/12.2307623

KEYWORDS: Sensors, Optical filters, Image compression, Spatial resolution, Image fusion, Satellites, Visualization, Optical components, Remote sensing, Data modeling

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In remote sensing, a common scenario involves the simultaneous acquisition of a panchromatic (PAN), a broad-band high spatial resolution image, and a multispectral (MS) image, which is composed of several spectral bands but at lower spatial resolution. The two sensors mounted on the same platform can be found in several very high spatial resolution optical remote sensing satellites for Earth observation (e.g., Quickbird, WorldView and SPOT)

In this work we investigate an alternative acquisition strategy, which combines the information from both images into a single band image with the same number of pixels of the PAN. This operation allows to significantly reduce the burden of data downlink by achieving a fixed compression ratio of 1/(1+b/p²) compared to the conventional acquisition modes. Here, b and p denote the amount of distinct bands in the MS image and the scale ratio between the PAN and MS, respectively (e.g.: b = p = 4 as in many commercial high spatial resolution satellites). Many strategies can be conceived to generate such a compressed image from a given set of PAN and MS sources. A simple option, which will be presented here, is based on an application of the color filter array (CFA) theory. Specifically, the value of each pixel in the spatial support of the synthetic image is taken from the corresponding sample either in the PAN or in a given band of the MS up-sampled to the size of the PAN. The choice is deterministic and done according to a custom mask. There are several works in the literature proposing various methods to construct masks which are able to preserve as much spectral content as possible for conventional RGB images. However, those results are not directly applicable to the case at hand, since it deals with i) images with different spatial resolution, ii) potentially more than three spectral bands and, iii) in general, different radiometric dynamics across bands. A tentative approach to address these issues is presented in this work. The compressed image resulting from the proposed acquisition strategy will be processed to generate an image featuring both the spatial resolution of the PAN and the spectral bands of the MS. This final product allows a direct comparison with the result of any standard pan-sharpening algorithm; the latter refers to a specific instance of data fusion (i.e., fusion of a PAN and MS image), which differs from our scenario since both sources are separately taken as input. In our setting, the fusion step performed at the ground segment will jointly involve a fusion and reconstruction problem (also known as demosaicing in the CFA literature). We propose to address this problem with a variational approach. We present in this work preliminary results related to the proposed scheme on real remote sensed images, tested over two different datasets acquired by the Quickbird and Geoeye-1 platforms, which show superior performances compared to applying a basic radiometric compression algorithm to both sources before performing a pan-sharpening protocol. The validation of the final products in both scenarios allows to visually and numerically appreciate the tradeoff between the compression of the source data and the quality loss suffered.

SPIE Journal Paper | 12 November 2015

Semiautomatic classification of cementitious materials using scanning electron microscope images

Lucas Drumetz, Mauro Mura, Samuel Meulenyzer, Sébastien Lombard, Jocelyn Chanussot

JEI, Vol. 24, Issue 06, 061109, (November 2015) https://doi.org/10.1117/12.10.1117/1.JEI.24.6.061109

KEYWORDS: Image segmentation, Cements, Image classification, Scanning electron microscopy, Image processing, X-rays, Electron microscopes, Image processing algorithms and systems, Denoising, Visualization

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Proceedings Article | 30 April 2015 Paper

Semi-automatic classification of cementitious materials using scanning electron microscope images

L. Drumetz, M. Dalla Mura, S. Meulenyzer, S. Lombard, J. Chanussot

Proceedings Volume 9534, 953403 (2015) https://doi.org/10.1117/12.2182762

KEYWORDS: Image segmentation, Cements, Denoising, Scanning electron microscopy, X-rays, X-ray imaging, Electron microscopes, Visualization, Stereolithography, Image classification

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Proceedings Article | 13 November 2012 Paper

High-performance computing in image registration

Michele Zanin, Fabio Remondino, Mauro Dalla Mura

Proceedings Volume 8539, 853902 (2012) https://doi.org/10.1117/12.981177

KEYWORDS: Image registration, Image processing, Signal processing, Feature extraction, Digital signal processing, Data modeling, Visualization, 3D modeling, Image resolution, Data acquisition

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Proceedings Article | 8 November 2012 Paper

Hierarchical watershed segmentation based on gradient image simplification

François Cokelaer, Mauro Dalla Mura, Jocelyn Chanussot

Proceedings Volume 8537, 85371O (2012) https://doi.org/10.1117/12.999358

KEYWORDS: Image segmentation, Image processing, Reconstruction algorithms, Remote sensing, Image filtering, Image processing algorithms and systems, Mathematical morphology, Chemical elements, Feature extraction, Filtering (signal processing)

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Proceedings Article | 8 November 2012 Paper

Detection of hedges based on attribute filters

Gabrielle Cavallaro, Benoit Arbelot, Mathieu Fauvel, Mauro Dalla Mura, Jón Atli Benediktsson, Lorenzo Bruzzone, Jocelyn Chanussot, David Sheeren

Proceedings Volume 8537, 853712 (2012) https://doi.org/10.1117/12.999360

KEYWORDS: Image filtering, Image processing, Image fusion, Sensors, Mathematical morphology, Image analysis, Multispectral imaging, Image quality, Environmental monitoring, Environmental sensing

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Proceedings Article | 8 November 2012 Paper

Integration of photogrammetric DSM and advanced image analysis for the classification of urban areas

Mauro Dalla Mura, Francesco Nex, Fabio Remondino, Michele Zanin

Proceedings Volume 8537, 85370U (2012) https://doi.org/10.1117/12.999359

KEYWORDS: Image classification, Scene classification, Buildings, RGB color model, Image processing, 3D image processing, 3D image reconstruction, Image analysis, Clouds, Image filtering

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Proceedings Article | 27 October 2011 Paper

Fusion of hyperspectral and lidar data using morphological attribute profiles

Mattia Pedergnana, Prashanth Marpu, Mauro Dalla Mura, Jon Atli Benediktsson, Lorenzo Bruzzone

Proceedings Volume 8180, 81801G (2011) https://doi.org/10.1117/12.899294

KEYWORDS: LIDAR, Electroactive polymers, Buildings, Hyperspectral imaging, Principal component analysis, Data fusion, Roads, Image fusion, Remote sensing, Data acquisition

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Proceedings Article | 23 October 2010 Paper

Study on the capabilities of morphological attribute profiles in change detection on VHR images

Nicola Falco, Mauro Dalla Mura, Francesca Bovolo, Jon Atli Benediktsson, Lorenzo Bruzzone

Proceedings Volume 7830, 783016 (2010) https://doi.org/10.1117/12.866178

KEYWORDS: Image filtering, Image resolution, Sensors, Image analysis, Earthquakes, Spatial resolution, Remote sensing, Filtering (signal processing), Data acquisition, Computer engineering

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Proceedings Article | 23 October 2010 Paper

Alternating sequential filters with morphological attribute operators for the analysis of remote sensing images

Mauro Dalla Mura, Jon Atli Benediktsson, Lorenzo Bruzzone

Proceedings Volume 7830, 783006 (2010) https://doi.org/10.1117/12.866232

KEYWORDS: Image filtering, Image processing, Image resolution, Remote sensing, Filtering (signal processing), Roads, Image analysis, Selenium, Buildings, Computer engineering

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Proceedings Article | 28 September 2009 Paper

Modeling structural information for building extraction with morphological attribute filters

M. Dalla Mura, J. Benediktsson, L. Bruzzone

Proceedings Volume 7477, 747703 (2009) https://doi.org/10.1117/12.836021

KEYWORDS: Image filtering, Image processing, Data modeling, Genetic algorithms, Image classification, Vegetation, Image resolution, Optimization (mathematics), Mathematical morphology, Feature extraction

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Showing 5 of 13 publications

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