Denoising method and device for quantum dot fluorescence image on surface of porous silicon biosensor

Abstract

The invention discloses a denoising method and device for a quantum dot fluorescence image on the surface of a porous silicon biosensor, and the method comprises the steps: analyzing the noise type in the quantum dot fluorescence image, and determining the noise type as gamma multiplicative noise; performing non-local mean smoothing processing on the obtained quantum dot fluorescence image, and taking the filtered image as a reference standard image for gray compression; obtaining a plurality of homogeneous regions of the noisy fluorescence image, averaging the variation coefficients of each homogeneous region to obtain an estimated variation coefficient, and determining the number of gray compression iterations; performing gray compression preprocessing on the noisy fluorescence image, taking the ratio of the smoothed image to the original fluorescence image as a compression coefficient, and performing compression according to the number of iterations; adopting a non-local anisotropic diffusion method, calculating the non-local cosine distance of each pixel point to obtain a threshold value of a diffusion coefficient, solving a differential equation to remove noisy points, and recovering an original gray value. The device comprises an analysis module, a smoothing module, an acquisition module, a compression module and a recovery module.

Description

technical field [0001] The invention relates to the field of image denoising, in particular to a method and device for denoising a quantum dot fluorescent image on the surface of a porous silicon biosensor. Background technique [0002] Nanoporous silicon is a new type of nanomaterial. Due to its large specific surface area, good biocompatibility, and adjustable refractive index, it can be prepared into high-sensitivity optical sensing devices with various structures, and has been widely used in biological detection. There are two main types of detection mechanisms of PSi optical sensors. The first category detects changes in the refractive index caused by biological reactions. The second category is the detection of fluorescence changes caused by biological reactions. The first type of detection usually employs reflectance spectrometers to measure shifts in the reflectance spectrum caused by biological responses. The second type of detection uses a spectrofluorometer to ...

AI Technical Summary

Problems solved by technology

[0005] Aiming at the problem of detection accuracy drop caused by gamma noise in quantum dot / porous silicon biodetection, the present invention provides a method and device for denoising quantum dot fluorescence images on the surface of porous silicon biosensors. The quantum dot fluorescence after processing in the present invention The noise is removed from the image, the original gray value of the image is restored to the greatest extent, and the sensitivity of biological detection based on quantum dot fluorescence image method is greatly improved. See the description below for details:

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