Sparse denoising and adaptive estimation enhances the resolution and contrast of fluorescence emission difference microscopy based on an array detector

Abstract

An array detector allows a resolution gain for confocal microscopy by combining images sensed by a set of photomultipliers tubes (or sub-detectors). Several methods have been proposed to reconstruct a high-resolution image by linearly combining sub-detector images, especially the fluorescence emission difference (FED) technique. To improve the resolution and contrast of FED microscopy based on an array detector, we propose to associate sparse denoising with spatial adaptive estimation. We show on both calibration slides and real data that our approach applied to the full stack of spatially reassigned detector signals, enables us to achieve a higher reconstruction performance in terms of resolution, image contrast, and noise reduction.