Image restoration for confocal microscopy: improving the limits of deconvolution, with application to the visualization of the mammalian hearing organ.

Deconvolution algorithms have proven very effective in conventional (wide-field) fluorescence microscopy. Their application to confocal microscopy is hampered, in biological experiments, by the presence of important levels of noise in the images and by the lack of a precise knowledge of the point spread function (PSF) of the system. We investigate the application of wavelet-based processing tools to deal with these problems, in particular wavelet denoising methods, which turn out to be very effective in application to three-dimensional confocal images. When used in combination with more classical deconvolution algorithms, these methods provide a robust and efficient restoration scheme allowing one to deal with difficult imaging conditions. To make our approach applicable in practical situations, we measured the PSF of a Biorad-MRC1024 confocal microscope under a large set of imaging conditions, including in situ acquisitions. As a specific biological application, we present several examples of restorations of three-dimensional confocal images acquired inside an intact preparation of the hearing organ. We also provide a quantitative assessment of the gain in quality achieved by wavelet-aided restorations over classical deconvolution schemes, based on a set of numerical experiments that we performed with test images.