Image deblurring based on fractional-order total variation and diffusion models
Image deblurring is a significant area of study in the field of digital image processing.In various practical applications,due to relative motion between imaging devices and objects,the resulting blurring will degrade the image quality and visual effect.This paper proposes an image deblurring method combining Fractional-order Total Variation(FTV)loss function and The enhancement of image structure information through probability modeling by DDPM,followed by the incorporation of the FTV loss function as a regular-ization term,facilitates the restoration of image details.Compared with traditional image deblurring methods,this method can restore more image detail while maintaining the overall image clarity.The experimental re-sults have verified that the method has the ability to restore images affected by motion blur.The significant su-periority provides a new direction for the further development of image deblurring.
Image debluringFractional calculusFractional-order total variationDenoising diffusion proba-bilistic models
国家科技期刊平台
NSTL
万方数据
