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1. US20120314920 - METHOD AND DEVICE FOR ANALYZING HYPER-SPECTRAL IMAGES

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Claims

1. A device for analyzing a hyper-spectral image, comprising:
at least one sensor able to produce a series of images in at least two wavelengths,
a calculation means able to class the pixels of an image according to a two-state classing relation, the image being received from the sensor and
a display means able to display at least one image resulting from the processing of the data received from the calculation means, wherein the calculation means comprises:
a means for determining training pixels linked to the two-state classing relation receiving data from a sensor,
a means for calculating a projection pursuit receiving data from the means for determining training pixels and being able to effect an automatic division of the spectrum of the hyper-spectral image, and
a means for producing a large-margin separation receiving data from the means for calculating a projection pursuit,
the calculation means being able to produce data relative to at least one enhanced image in which the pixels obtained following the large-margin separation are distinguishable as a function of their classing according to the two-state classing relation.
2. The analysis device as claimed in claim 1, comprising a mapping of classed pixels linked to the means for determining training pixels.
3. The analysis device as claimed in claim 1, in which the means for calculating a projection pursuit comprises a first dividing means, a second dividing means and a means for searching for projection vectors.
4. The analysis device as claimed in claim 1, in which the means for calculating a projection pursuit comprises a dividing means with a constant number of bands and a means for searching for projection vectors.
5. The analysis device as claimed in claim 4, in which the means for calculating a projection pursuit comprises a means for shifting the boundaries of each group resulting from the dividing means with a constant number of bands, the shifting means being able to minimize the internal variance of each group.
6. The analysis device as claimed in claim 1, in which the means for calculating a projection pursuit comprises a dividing means with automatic determination of the number of bands as a function of predetermined thresholds and a means for searching for projection vectors.
7. The analysis device as claimed in claim 6, in which the means for determining training pixels is able to determine the training pixels as the pixels nearest to the thresholds.
8. The analysis device as claimed in claim 1, in which the means for producing a large-margin separation comprises a means for determining a hyperplane, and a means for classing pixels as a function of their distance to the hyperplane.
9. The analysis device as claimed in claim 1, in which the calculation means is able to produce an image that can be displayed by the display means as a function of the hyper-spectral image received from a sensor and the data received from the means for producing a large-margin separation.
10. A method for analyzing a hyper-spectral image originating from at least one sensor able to produce a series of images in at least two wavelengths, comprising:
a step of acquisition of a hyper-spectral image by a sensor,
a step of calculation of the classing of the pixels of a hyper-spectral image received from a sensor according to a two-state classing relation, the display of at least one enhanced image resulting from the processing of the data from the step of acquisition of a hyper-spectral image and the data from the step of calculation of the classing of the pixels of a hyper-spectral image, wherein the calculation step comprises:
a step of determination of training pixels linked to the two-state classing relation,
a step of calculation of a projection pursuit of the hyper-spectral image comprising the training pixels, comprising an automatic division of the spectrum of said hyper-spectral image, and
a large-margin separation step,
the calculation step being able to produce at least one enhanced image in which the pixels obtained following the large-margin separation are distinguishable as a function of their classing according to the two-state classing relation.
11. The analysis method as claimed in claim 10, in which the step of determination of training pixels comprises the determination of training pixels as a function of data from a mapping, the step of determination of training pixels furthermore comprising the introduction of said training pixels into the hyper-spectral image received from a sensor.
12. The analysis method as claimed in claim 11, in which the step of calculation of a projection pursuit comprises a first division step relating to the data resulting from the step of determination of training pixels and a step of searching for projection vectors.
13. The analysis method as claimed in claim 12, in which the step of calculation of a projection pursuit comprises a second division step if the distance between two images resulting from the first division step is greater than a first threshold, or if the maximum value of the distance between two images resulting from the first division step is greater than a second threshold.
14. The analysis method as claimed in claim 10, in which the step of calculation of a projection pursuit comprises a division with a constant number of bands.
15. The analysis method as claimed in claim 14, in which the boundaries of each group resulting from the division with a constant number of bands can be shifted in order to minimize the internal variance of each group.
16. The analysis method as claimed in claim 10, in which the step of calculation of a projection pursuit comprises a division with automatic determination of the number of bands as a function of predetermined thresholds.
17. The analysis device as claimed in claim 16, in which the step of determination of training pixels comprises a determination of the training pixels as the pixels nearest to the thresholds.
18. The analysis method as claimed in claim 10, in which the large-margin separation step comprises a step of determination of a hyperplane, and a step of classing of the pixels as a function of their distance to the hyperplane, the step of determination of a hyperplane relating to the data resulting from the projection pursuit calculation step.
19. An application of an analysis device as claimed in claim 9 to the detection of skin lesions of a human being, the hyperplane being determined as a function of training pixels resulting from previously analyzed templates.