一种基于退化竞争的活性污泥微生物图像去模糊增强方法
By constructing multiple degradation kernel libraries and adaptive fuzzy kernel models, the problem of inconsistent degradation types in different regions of activated sludge microscopic images was solved, and the image clarity and structural continuity were improved, making it suitable for microbial image analysis in wastewater treatment.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- UNIV OF JINAN
- Filing Date
- 2026-05-22
- Publication Date
- 2026-07-17
AI Technical Summary
Existing microscopic image enhancement methods are ill-suited to addressing the inconsistent degradation patterns in different regions of activated sludge microscopic images. This makes it difficult to clearly identify microbial outlines, cilia, flagella, and other structures, affecting the accuracy of subsequent observation and analysis.
We constructed a confidence map of microbial structure, a background interference map of flocculent material, and a response map of slender structure. We established a candidate degenerate kernel library of microscopic out-of-focus blur kernel, liquid disturbance motion blur kernel, and random jitter blur kernel. We generated degenerate competition weights by restoring local residuals, generated spatial adaptive blur kernels, and constructed a variational deblurring energy model for image enhancement.
It improves the clarity and structural continuity of activated sludge microbial images, reduces interference from complex backgrounds, and enhances the accuracy and stability of image analysis, making it suitable for monitoring the operational status of wastewater treatment plants.
Smart Images
Figure CN122243814B_ABST