AR-PAM image enhancement and noise reduction method based on Mean-reverting diffusion model

By adopting the forward and reverse diffusion processes of the Mean-reverting diffusion model in AR-PAM technology, combined with the training of noise network, the problems of low image resolution and serious noise interference are solved, efficient denoising and image detail recovery are achieved, and image quality is significantly improved.

CN119648554AActive Publication Date: 2025-03-18NANCHANG UNIV
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Patent Information

Application Number
CN202510173606.3
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-02-18
Publication Date
2025-03-18
Estimated Expiration
2045-02-18

AI Technical Summary

Technical Problem

The existing AR-PAM technology cannot clearly image when the lateral resolution is low and the noise interference is severe, and traditional image processing methods have problems such as excessive smoothing, loss of detail and computational complexity.

Method used

The forward and reverse diffusion process based on the Mean-reverting diffusion model is adopted to estimate the score function by training the noise network, thereby guiding the reverse generation and denoising of the image and improving the lateral resolution and overall quality of the AR-PAM image.

Benefits of technology

It realizes efficient noise denoising and image detail recovery while maintaining computing efficiency, significantly improving the resolution and clarity of AR-PAM images, and is suitable for a variety of practical application scenarios.

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Abstract

The invention discloses an AR-PAM (Auto Register-Pulse Amplitude Modulation) image enhancement and noise reduction method based on a Mean-reverting diffusion model. According to the method, through a diffusion process of reverse SDE, a Mean-reverting diffusion model is utilized to convert a high-resolution image into a fixed Gaussian noise state, and an original high-resolution image is recovered through the reverse SDE process, so that resolution enhancement and noise suppression of the AR-PAM image are realized. Compared with a traditional method, the method has the advantages that the transverse resolution of the image can be remarkably improved on the premise that the AR-PAM imaging depth is not sacrificed, and noise is effectively restrained. Through verification of simulation data and in-vivo experiment data, the method provided by the invention shows an excellent enhancement effect in various degradation scenes, and especially under the conditions of high noise and low resolution, the peak signal-to-noise ratio and the structural similarity of the image can be remarkably improved, and the image quality is improved. Therefore, a new possibility is provided for application expansion of the photoacoustic microscopic imaging technology.
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