基于全变分模型的并行图像增强研究

Parallel Image Enhancing Research Based on PDE

全变分模型(TV)是利用偏微分方程(PDE)方法处理图像的一种模型,特别是在图像增强中,能较好地抑制噪声、保留图像原有的边缘和纹理。但由于PDE的差分求解运算量大,当处理的图像像素值较大时,计算速度不能满足实时系统需要。文章针对该模型,利用像素独立性和PDE求解的并发性,采用并行方式增强图像,改善了计算时间。

Total Variation(TV) is one of image processing methods by using Partial Differential Equation(PDE),it can restrain noise fairly good,reserve original edge and texture,especially for image enhancement.However,the computing size of the PDE is huge when the image pixel is big and the time cost of computing is important for the real time system.For the TV methods,parallel computing could reduce the computing time by using independence of image pixel and subsequent of PDE.