In view of the fact that digital images are prone to blur during processing, an adaptive deconvolution deblurring algorithm based on non-reference image quality evaluation is proposed. Firstly, according to the strong correlation between the no-reference image quality evaluation result and its distortion level, we can determine the fuzzy level of the image by calculating the no-reference image quality evaluation value and finally determine the convolution kernel with the linear relationship between the image fuzzy level and the fuzzy kernel. In order to ensure the fidelity of the color image before and after color processing and improve the efficiency of the algorithm, we propose to transform the distorted image color space to YUV, and only process the Y-channel in the distorted image. The Gibbs-like oscillation distribution phenomenon occurs in the neighborhood of sharp changes in the image gray levels. Gradient-based weight matrix is proposed to control the phenomenon. Experimental results show that the proposed algorithm can not only quickly and effectively remove the image blur, but also effectively retain the texture details of the restored image.