1. A method for estimating an input signal (x(t)) representative of a feature of physical quantity measured by a sensor device ( 100 ), said sensor device ( 100 ) having a response function described by an a priori known convolution kernel (N(t)) and outputting a noisy measured signal (y(t)) which is considered as the sum of, in one hand, the convolution product (x(t) N(t)) of said input signal (x(t)) and said convolution kernel (N(t)) and, in the other hand, a noise (no) which interferes with the measure, said method being carried out by deconvoluting said noisy measured signal (y(t)), characterised in that said method comprises an estimate computation step ( 400 ) including computing of a minimal estimate of the convolution product of the input signal (x min (t)) by the convolution kernel (N(t)) of the sensor device ( 100 ) in order that said minimal estimate is lower than or equal to the noisy measured signal (y(t)), computing of a maximal estimate of the convolution product of the input signal by the convolution kernel of the sensor device in order that said maximal estimate is greater than or equal to the noisy measured signal (y(t)), and computing of a final estimate of the convolution product as being the average of said minimal and maximal estimates of the convolution product, and a deconvolution step for deconvolving said final estimate of the convolution product in order to estimate the input signal (x(t)).