Improving PSF calibration in confocal microscopic imaging---estimating and exploiting bilateral symmetry

A method for estimating the axis of reflectional symmetry of an image $f(x,y)$ on the unit disc $D=\{(x,y):x^2+y^2\leq1\}$ is proposed, given that noisy data of $f(x,y)$ are observed on a discrete grid of edge width $Δ$. Our estimation procedure is based on minimizing over $β\in[0,π)$ the $L_2$ distance between empirical versions of $f$ and $τ_βf$, the image of $f$ after reflection at the axis along $(\cosβ,\sinβ)$. Here, $f$ and $τ_βf$ are estimated using truncated radial series of the Zernike type. The inherent symmetry properties of the Zernike functions result in a particularly simple estimation procedure for $β$. It is shown that the estimate $\hatβ$ converges at the parametric rate $Δ^{-1}$ for images $f$ of bounded variation. Further, we establish asymptotic normality of $\hatβ$ if $f$ is Lipschitz continuous. The method is applied to calibrating the point spread function (PSF) for the deconvolution of images from confocal microscopy. For various reasons the PSF characterizing the problem may not be rotationally invariant but rather only reflection symmetric with respect to two orthogonal axes. For an image of a bead acquired by a confocal laser scanning microscope (Leica TCS), these axes are estimated and corresponding confidence intervals are constructed. They turn out to be close to the coordinate axes of the imaging device. As cause for deviation from rotational invariance, this indicates some slight misalignment of the optical system or anisotropy of the immersion medium rather than some irregular shape of the bead. In an extensive simulation study, we show that using a symmetrized version of the observed PSF significantly improves the subsequent reconstruction process of the target image.

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