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.