In this article, we propose a variational PDE model using $\ell_2-\ell_p$ regulariser for removing Poisson noise in presence of blur. The proposed minimization problem is solved using augmented Lagrangian method. The convergence of the sequence of minimizers have been carried out. Numerical simulations on some standard test images have been shown. The numerical results are compared with that of a few models existed in literature in terms of image quality metric such as SSIM, PSNR and SNR.

翻译：本文提出了一种利用$\ell_2-\ell_p$正则化器的变分偏微分方程模型，用于在存在模糊的情况下去除泊松噪声。所提出的最小化问题通过增广拉格朗日法求解。本文对极小化序列的收敛性进行了分析，并在若干标准测试图像上进行了数值模拟。通过SSIM、PSNR和SNR等图像质量指标，将数值结果与文献中已有的若干模型进行了比较。