二次稀疏极端通道先验盲超声图像去模糊

Blind Ultrasound Image Deblurring via Quadratic Sparse Extreme Channel Prior

模糊的超声图像经过极端通道先验去模糊后不够稀疏,导致极端通道稀疏约束可能不存在。因此,为了充分利用图像通道信息,通过增强去模糊后超声图像的稀疏性,提出一种二次稀疏极端通道先验盲超声图像去模糊算法。首先,给出了相关的理论证明和实验说明二次稀疏极端通道先验用于约束模糊超声图像的可行性;然后,充分利用暗通道和亮通道的先验信息,在交替迭代过程中采用半二次分裂方法估计中间图像和模糊核;最后,用傅里叶变换求得最终的清晰图像和模糊核。在超声图像集上的实验结果表明,本文提出的二次稀疏极端通道先验盲超声图像去模糊算法和其他超声图像去模糊方法相比更具可行性和优越性。

The blurry ultrasound image is not sparse enough after the extreme channel prior deblurring,resulting in the extreme channel sparse constraint may not exist.Therefore,in order to make full use of the image channel information,a blind ultrasound image deblurring algorithm via quadratic sparse extreme channel prior is proposed by enhancing the sparsity of the obtained ultrasound image after deblurring.First,relevant theoretical proofs and experiments are presented to illustrate the feasibility of quadratic sparse extreme channel priors for constrained blurry ultrasound images.Then,making full use of the prior information of the dark and bright channels,the half-quadratic splitting method is used to estimate the intermediate image and the blur kernel.Finally,the Fourier transform is used to obtain the final clear image and blur kernel.Experimental results on the ultrasound image set show that the feasibility and superiority of the proposed algorithm compared other current ultrasound image deblurring methods.