Abstract
We propose and demonstrate a novel subtraction microscopy algorithm, exploiting fluorescence emission difference or switching laser mode and their derivatives for image enhancement. The key novelty of the proposed approach lies in the weighted subtraction coefficient, adjusted pixel-by-pixel with respect to the intensity distributions of initial images. This method produces significant resolution enhancement and minimizes image distortions. Our theoretical and experimental studies demonstrate that this approach can be applied to any optical microscopy techniques, including label free and non-linear methods, where common super-resolution techniques cannot be used.
Highlights
As an alternative solution, an image subtraction approach was proposed for the contrast and resolution enhancement in laser scanning microscopy techniques, known as switching laser mode (SLAM) or fluorescence emission difference (FED)[9,10]
For SLAM and FED microscopy, the resulting image is obtained by intensity subtraction, as follow: Ifinal = IGauss − αI dnut where Ifinal, IGauss and Idnut are the normalized intensity distributions of the resulting image, and the Gaussian and doughnut measurements, respectively
We propose the intensity-weighted subtraction (IWS) method, where the subtraction coefficient, α, is assigned at each pixel based on the intensity distribution of the initial images
Summary
As an alternative solution, an image subtraction approach was proposed for the contrast and resolution enhancement in laser scanning microscopy techniques, known as switching laser mode (SLAM) or fluorescence emission difference (FED)[9,10] Both techniques are based on the concept that two images are taken with Gaussian and doughnut shaped excitation beams, and afterwards the images are subtracted from each other with an appropriate normalizing coefficient. Defocus or aberrations can result in negative values for the transfer function[18], and polarization can have a similar effect[19] Deconvolution is another image post processing approach which can provide good resolution enhancement up to factor of two in some cases[20]. There is a necessity of studying the image processing techniques, such as subtraction, which do not require prior information
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