Self-adaptation morphological filtering system and method applied to calorescence correlation imaging

Abstract

The invention discloses a self-adaptation morphological filtering system and a method applied to calorescence correlation imaging. The method includes the following steps: binarization processing on related images to form binary system grayscale images; corrosion on the binary system grayscale images through a morphological filter by utilizing structural elements in certain sizes to remove spots produced by the related images, and therefore pixels on object boundaries can be eliminated; median filtering on the corroded binary system grayscale images so as to remove noise; and closed operation and expansion operation on the binary system grayscale images to achieve the purpose of regaining original images. By means of the self-adaptation morphological filtering system and the method applied to the calorescence correlation imaging, good imaging effect comparing with images of lowpass filtering, average filtering and median filtering is achieved.

Description

technical field [0001] The present invention relates to an adaptive morphological filtering system and method, in particular to an adaptive morphological filtering system and method applied to thermo-optic correlation imaging. Background technique [0002] Optical imaging is a well-known fundamental physical phenomenon that reflects the nature of waves. Since the 1980s, in the theoretical and experimental research on the two-photon entangled state generated by the spontaneous parametric down-conversion process of nonlinear crystals, some new optical phenomena have been discovered, such as correlated imaging and correlated interference. The researchers are mainly working on the theoretical value of correlative imaging. However, the quality of correlative imaging is often relatively poor and contains a lot of noise. The methods of processing correlative imaging at home and abroad generally include low-pass filtering, mean filtering, median filtering and other methods. [000...

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Problems solved by technology

[0004] In the processing of associated imaging by mean filtering, the original image is filtered by 3*3, 6*6, and 9*9 respectively, and it is found that the more noise is filtered out, the blurrier the original image will be. This processing method has defects, and the mean The function of filtering is to smooth the image. During the processing, not only the noise is smoothed, but the

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