一种改进的基于KRR的单帧图像超分辨率重建算法

An Improved Super Resolution Reconstruction Algorithm of Single Image Based on KRR

为解决图像超分辨率重建结果中的图像质量问题,论文提出了一种改进的基于核岭回归(Kernel Ridge Regres-sion,KRR)的单帧图像超分辨率重建算法。该算法利用核岭回归算法估计潜在的高分辨率图像中高频细节信息,然后将核匹配追踪算法与梯度下降算法相结合,得到一种基于稀疏表示的对KRR进行求解的方法,再使用一个通用的图像先验模型对回归结果进行处理,用以消除正则化过程中产生的振铃,进而得到最终的高分辨率重建图像。实验结果证明,该方法在时间复杂度保持中等水平的同时具有良好的重建效果。

To solve the problem of image quality in image super resolution reconstruction, this paper proposes an improved algorithm of single image super resolution reconstruction based on Kernel Ridge Regression （KRR）. The algorithm uses KRR estimation of high-frequency information of potential high resolution image, then the kernel matching pursuit algorithm and gradient de- scent algorithm are combined to obtain a sparse representation based method for solving KRR. To solve the problem of ringing artifactsoccurring due to the regularization effect, the regression results are post-processed using a prior model of a generic image class, then gets the final high resolution reconstruction image. Experimental results demonstrate that the method has good reconstruction quality in the condition of keeping the time complexity of medium level.