Computer implemented method to determine a point spread function PSF xy as a 2-dimensional matrix in the shape and size of a peripheral sensing kernel k ixj of a digital image detector system, comprising the steps of: - acquiring a set of image pixel values comprising transfer function modulated quantum noise in a spatial sample area R[x',y'] of a digital image I [ X,Y] that is exposed such that there are no clear intended structural objects visible in said image that cause image signal variations against the recorded background of more than 1%, - determine the peripheral sensing kernel k i × j wherein the pixel values matrix k [ x,y] is centred on a central pixel, - calculating for each local image pixel L ( x,y) in said sample area R [ x',y']: -- a pixel deviation Δ L between a pixel value at pixel L ( x,y) and its background value val ( B L), wherein val ( B L) is defined as the median or mean value of all values in a background region B L centred on said local pixel L ( x,y), and -- a median or mean pixel deviation Δ N d of all background normalized neighbouring pixels values val ( N d (1 →n)) = val ( N d 1), val ( N d 2),..., val ( N dn) that are located at the same distance d from said local image pixel L ( x,y) and that are normalized against their respective background value val ( B N d ( i)), wherein val ( B N d ( i)) is defined as the median value of all pixel values in a background region B N d ( i) centred on said neighbouring pixels N d ( i), - calculating an autocorrelation peak value by autocorrelating Δ L for all local pixels L(x,y) in the sample area R [ x',y'], as AutoCorrelationPeak R x ′ y ′ = ∑ ∑ x = 0, y = 0 R x ′ y ′ ΔL 2 - calculating PSF xy as PSF N d = Correlation ΔL, Δ N ̅ d AutoCorrelationPeak R x ′ y ′ where Correlation (Δ L, Δ N d) is obtained by correlating Δ L with Δ N d for a distance d from local pixel L(x,y), and by summing the results over all pixels in the sample area R [ x',y'], Correlation ΔL, Δ N ̅ d = ∑ ∑ x = 0, y = 0 R x ′ y ′ ΔL. Δ N ̅ d - acquiring a set of image pixel values comprising transfer function modulated quantum noise in a spatial sample area R[x',y'] of a digital image I [ X,Y] that is exposed such that there are no clear intended structural objects visible in said image that cause image signal variations against the recorded background of more than 1%, - determine the peripheral sensing kernel k i × j wherein the pixel values matrix k [ x,y] is centred on a central pixel, - calculating for each local image pixel L ( x,y) in said sample area R [ x',y']: -- a pixel deviation Δ L between a pixel value at pixel L ( x,y) and its background value val ( B L), wherein val ( B L) is defined as the median or mean value of all values in a background region B L centred on said local pixel L ( x,y), and -- a median or mean pixel deviation Δ N d of all background normalized neighbouring pixels values val ( N d (1 →n)) = val ( N d 1), val ( N d 2),..., val ( N dn) that are located at the same distance d from said local image pixel L ( x,y) and that are normalized against their respective background value val ( B N d ( i)), wherein val ( B N d ( i)) is defined as the median value of all pixel values in a background region B N d ( i) centred on said neighbouring pixels N d ( i), -- a pixel deviation Δ L between a pixel value at pixel L ( x,y) and its background value val ( B L), wherein val ( B L) is defined as the median or mean value of all values in a background region B L centred on said local pixel L ( x,y), and -- a median or mean pixel deviation Δ N d of all background normalized neighbouring pixels values val ( N d (1 →n)) = val ( N d 1), val ( N d 2),..., val ( N dn) that are located at the same distance d from said local image pixel L ( x,y) and that are normalized against their respective background value val ( B N d ( i)), wherein val ( B N d ( i)) is defined as the median value of all pixel values in a background region B N d ( i) centred on said neighbouring pixels N d ( i), - calculating an autocorrelation peak value by autocorrelating Δ L for all local pixels L(x,y) in the sample area R [ x',y'], as AutoCorrelationPeak R x ′ y ′ = ∑ ∑ x = 0, y = 0 R x ′ y ′ ΔL 2 - calculating PSF xy as PSF N d = Correlation ΔL, Δ N ̅ d AutoCorrelationPeak R x ′ y ′ where Correlation (Δ L, Δ N d) is obtained by correlating Δ L with Δ N d for a distance d from local pixel L(x,y), and by summing the results over all pixels in the sample area R [ x',y'], Correlation ΔL, Δ N ̅ d = ∑ ∑ x = 0, y = 0 R x ′ y ′ ΔL. Δ N ̅ d