Weak luminescence image processing method based on regional augmentation and regional extraction

Abstract

The invention relates to a weak luminescence image processing method based on regional augmentation and regional extraction in the technical field of image processing. The method comprises the following steps: converting unidimensional original data sequence of a background image and an original weak luminescence image under the lighting condition into a two-dimensional array structure, and carrying out logarithm transformation on the two-dimensional array structure; then removing noise of the weak luminescence image through morphological weighting median filtering, extracting a boundary of the weak luminescence image by a Canny differential operator, and then filling a weak luminescent region by a boundary closely extracted by a morphological template; obtaining a binary image with a marked weak luminescent region; checking a weak luminescent region of the image, and superposing the region onto the background image with lighting condition after pseudo color treatment; adding a marker on the image brightness by an image luminescent illumination calibration method; and finally recording image experimental conditions, image source and other additional information. The invention provides the reliable weak luminescence image processing method and realizes a treating process from inputting original image data sequence to outputting an image result.

Description

technical field [0001] The invention relates to a method in the technical field of image processing, in particular to a method for processing weakly luminescent images based on region enhancement and region extraction. Background technique [0002] In weak luminescence imaging, in order to make the original weak luminescence image of the detected sample output by the imaging detection sensor clearly and intuitively provided to experimental researchers for viewing, a series of processing is required. At present, the general method is to first collect the weak luminescence of the detected sample by the imaging detection sensor, convert the input one-dimensional weak luminescence signal sequence into a two-dimensional luminescence image, and then perform denoising processing on the original luminescence image, and collect another image with illumination The sample overview image under the condition is used as the background image, and the region of interest in the previous imag...

AI Technical Summary

Problems solved by technology

This technology uses the threshold method to segment images. Although a function that can be adjusted manually is added, it is difficult to distinguish the luminous area from the noise background when the weak luminescent imaging area is submerged in the noise signal by a single threshold segmentation, especially in high Sensitivity When optical imaging equipment detects extremely weak luminescence and needs to adjust high-sensitivity imaging parameters, it is more likely to cause detection noise or the signal emitted by the noise of the imaging detector itself will be closer to the brightness of the luminescence signal of the target, so a single threshold segmentation method will be difficult to work

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