Linear Filtering and Total Variation De-noising of Composite Noises: Different Architectures and Simulation Study

摘要

Combined techniques consisting of traditional linear filtering and total variation de-noising are studied to de-noise images polluted with composite noises from different sources. Series and parallel approaches are compared theoretically. Some further discussions are given about parameters and their effect on the optimization problem. A simultaneous method is proposed and simulated using the convex optimization toolbox, comparing different alternative methods with respect to signal to noise ratio and error covariance matrix. The proposed method could be used to enhance the smoothing performance.