Sagem Defense Securite

Safran Electronics & Defense

Marc Bousquet

Nicolas Roux

Philippe Foubert

Thierry Touati

Maxime Thiebaut

Christophe Guettier

Francois Dufresne De Virel

Jacques Yelloz

Sylvain Negroni

Guillaume Magniez

François Dufresne De Virel

Frédéric Berthault

Jean-Marc Champeyroux

Method for collaborative observation between a local targeting device and a distant targeting device located at different geographical positions and able to acquire images. The method including: when it is implemented by the local targeting device, execution of a procedure for determining a position of an observed object, referred to as the local targeted object, including application of a method for matching points of interest, determined on a local image by the local targeting device, representing a distant image obtained from the distant targeting device. If matching is successful, the local targeting device determines the position of the local targeted object according to information representing a position of a distant targeted object supplied by the distant targeting device and a transformation law allowing to pair the distant and local points of interest obtained when said matching method is applied and controls display of an image comprising the local targeted object.

Collaborative targeting method

A decamouflaging method includes: obtaining image representing a scene including a multispectral image including components in the spectral domain ranging from the visible domain to the short-wavelength infrared and a thermal image including a component in the medium infrared and/or the long-wavelength infrared; extracting a sub-part ('window') from each of the images obtained at a given position; applying a contrast accentuation procedure to the window extracted from the multispectral image allowing an improved window to be obtained where contrast between pixels corresponding to the object and pixels not corresponding to the object is accentuated; forming a multicomponent window, the improved window obtained and the window extracted from the thermal image each supplying a component of the multicomponent window; and applying the procedure to the multicomponent window; generating an image by inserting the improved window obtained by applying the procedure to the multicomponent window in a receiving image representing the scene.

Method for decamouflaging an object

A movement detection device, including a multi-element photodiode, the multi-element photodiode comprising a plurality of pixels, referred to as megapixels, and, for at least one megapixel of the multi-element photodiode, a mask partially obscuring a sensitive zone of said megapixel, the mask consisting of a plurality of zones including at least one opaque zone and at least one transparent zone, an opaque zone being able to prevent a light beam from fully reaching portions of the sensitive zone of the megapixel corresponding to the opaque zone, a transparent zone being able to allow a light beam to reach a portion of the sensitive surface of the megapixel corresponding to the transparent zone, each opaque zone having at least one adjacent transparent zone so as to obtain an alternation of opaque zones and transparent zones in the mask.

Movement detection device

The invention relates to a method for analyzing a multispectral image (), which includes designing a detection image from the values of a revealing function that quantifies a content shift in the multispectral image between two areas. The revealing function is applied between a target area and a background area, inside a window which is determined around each pixel. The revealing function values are determined from integral images of order one, and optionally also of order two, which in turn are calculated only once initially, so that the total amount of calculations is reduced. The analysis method is compatible with a real-time implementation during a capture of consecutive multispectral images which form a video stream, in particular for an environment-monitoring task.

Analysis of a multispectral image

The invention relates to a method for analyzing a multispectral image (), which includes designing a detection image from signal-to-noise ratio values. The signal-to-noise ratio values relate to the content of the multispectral image inside a window which is determined around each pixel, when the contrast in the window is maximized by a Fischer projection. The signal-to-noise ratio values at calculated from integral images of order one and two, which in turn are calculated only once initially, so that the total amount of calculations is reduced. The analysis method is compatible with a real-time implementation during a capture of consecutive multispectral images which form a video stream, in particular for an environment-monitoring task.

The invention relates to a system for detection and infrared imaging by spectral analysis in several wavelength bands comprising: &#x2014;an imaging sensor comprising a plurality of elementary sensors together forming a matrix sensitive surface; &#x2014;an imaging optic adapted for forming on the sensitive surface of the imaging sensor, a first image of the scene to be analyzed in a first wavelength band, and at least one second image of the scene to be analyzed in a second wavelength band, characterized in that said detection and imaging system furthermore comprises an optical device consisting of a fixed optical plate adapted for shifting the first image with respect to the second image in the plane of the sensitive surface, the shift between the images being along a direction defined by a row, a column or a diagonal of elementary sensors, the shift distance being equal to the spacing of the elementary sensors of the matrix sensitive surface along this direction or to a multiple of this spacing.

System for detection and imaging by spectral analysis in several wavelength bands

Images captured by an image capture device on a line of sight with an associated gyrometric system designed to supply gyrometric measurement data relating to the line of sight are stabilized. To this end, a first series of captured images is obtained. Then, a second series of stabilized images is obtained by applying, to the first series of images, an image stabilization based on gyrometric information. Then, a residual stabilization error is determined by applying a digital processing to the second series of stabilized images. Finally, the preceding three steps are repeated. On initialization, the gyrometric information corresponds to the measurement data supplied by the gyrometric system. Then, subsequently, the gyrometric information is obtained by correcting, on the basis of the residual error, the measurement data supplied by the gyrometric system.

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Boulogne-Billancourt, France

Marc Bousquet