TV-Retinex:a Fast Algorithm for Image Enhancement

In this paper,a fast algorithm based on Retinex theory for color image enhancement is proposed.A total variational framework is employed,in which L₁ norm instead of the original L₂ norm is adopted.As a convex functional,the proposed model gives the solution of global optimization.The split Bregman method is employed to compute our model with high efficiency.In addition to its computational efficiency,our model is also good at preserving texture details and color information of the image.The proposed method is compared with two popular methods in terms of enhancement performance and computational efficiency.The experimental results show that the proposed method is nearly 40 times faster than the original methods with comparable enhancement performance.