Abstract:

In order to preserve more image details information while image denoising, the concept of fractionalorder gradient descent flow is proposed by combining fractional calculus and gradient descent flow, and the fractional order gradient descent flow of an energy function is convergent within a certain range of differential order. On this base, the denoising model based on timespace fractional partial equations is constructed by adding a time factor to the improved denoising model based on space fractional partial equations. The proposed denoising model can be implemented to remove noise at the time and space direction simultaneously. The experimental results show that, compared with the existing denoising model, the improved image denoising model based on timespace fractional partial differential equations could make the visual effect better and has a faster computing speed. In addition, compared with the image denoising model based on space fractional partial differential equations, the image denoising model based on time-space fractional partial differential equations can appropriately increase the signal-to-noise ratio of images and significantly reduce the iteration number under the condition that the signal-to-noise ratio of the denoising image getting the maximum.