We propose a novel method by combining the total variation (TV) with the high-degree TV (HDTV) to improve the reconstruction quality of sparse-view sampling photoacoustic imaging (PAI). A weighing function is adaptively updated in an iterative way to combine the solutions of the TV and HDTV minimizations. The fast iterative shrinkage/thresholding algorithm is implemented to solve both the TV and the HDTV minimizations with better convergence rate. Numerical results demonstrate the superiority and efficiency of the proposed method on sparse-view PAI. In vitro experiments also illustrate that the method can be used in practical sparse-view PAI.