1. A method for analyzing a multispectral image, said multispectral image comprising a plurality of spectral images of the same scene but corresponding to different spectral ranges, each spectral image assigning an intensity value to each pixel located at an intersection of a row and a column of a matrix of the multispectral image, and an origin point being defined at a corner of the peripheral boundary of the matrix; wherein a detection image is constructed by assigning a display value to each pixel of a working area of the matrix, said display value being obtained from a signal-to-noise ratio calculated for said pixel; the method comprising the steps of: /1/ for each spectral image, calculating a first-order integral image by assigning to each calculation pixel an integral value equal to the sum of the intensity values of said spectral image for all pixels contained within a rectangle having two opposite vertices respectively located on the origin point and on the calculation pixel; and for each pair of spectral images obtained from the multispectral image, calculating a second-order integral image by assigning to each calculation pixel another integral value equal to the sum, for all pixels contained within the rectangle having two opposite vertices respectively located on the origin point and on said calculation pixel, of products of the two intensity values relative to the same pixel but respectively assigned by each spectral image of the pair; /2/ defining a fixed window frame and a mask internal to the frame, said mask defining a target area and a background area within the frame; and /3/ for each pixel of the working area of the matrix: /3-1/ placing the window at a position in the matrix that is determined by the pixel, the window being delimited by the frame defined in step /2/; /3-2/ determining a Fisher factor, in the form of a vector associated with a Fisher projection which increases a contrast of the multispectral image in the window between the target area and the background area; and /3-3/ calculating from the integral values read from the first- and second-order integral images: two mean vectors, for the target area and for the background area respectively, each having a coordinate, for each spectral image, which is equal to the mean of the intensity values of said spectral image, calculated for the pixels of the target area or of the background area respectively; a mean matrix, having a factor for each pair of spectral images which is equal to the mean of the products of the two intensity values relative to each pixel but respectively assigned by each spectral image of the pair, calculated for the pixels of the background area; /3-4/ then calculating: two mean Fisher values, mF T and mF B , for the target area and for the background area respectively, each equal to the dot product of the Fisher factor and of the mean vector for the target area or for the background area respectively; a Fisher variance over the background area, VarF B , equal to the quadratic product of the mean matrix and of the Fisher factor, decreased by the square of the Fisher mean for the background area; and /3-5/ calculating the signal-to-noise ratio for the pixel of the working area, equal to [(mF T −mF B ) 2 /VarF B ] 1/2 ; and wherein the display value is obtained from the signal-to-noise-ratio for each pixel in the detection image, using one or a combination of the following methods: comparing the signal-to-noise ratio to a threshold, and the display value is set to zero if this signal-to-noise ratio is below the threshold, otherwise the display value is set to said signal-to-noise ratio; or applying a linear scale conversion to the signal-to-noise ratio, and the display value is set to a result of this conversion.