A novel local and nonlocal total variation combination method for image restoration in wireless sensor networks

Abstract

In this paper, we propose a novel local and nonlocal total variation combination method for image restoration in wireless sensor networks (WSN), which plays an important role in improving the quality of the transmitted image. First, the degrade image is preprocessed by an image smoothing scheme to divide the image into two regions. One contains edges and flat regions by the local TV term. The other is rich in image details and regularized by the nonlocal TV term. Then, the alternating direction method of multipliers (ADMM) algorithm is adopted to optimize the complex object function, and two key parameters are discussed for better performance. Finally, we compare our method with several recent state-of-the-art methods and illustrate the efficiency and performance of the proposed model by experimental results in peak signal to noise ratio (PSNR) and computing time.

Survey of Super Resolution Techniques

“…Shi [33] proposed a novel local and nonlocal total variation combination method for image restoration in wireless sensor networks (WSN). The degraded image is preprocessed by an image smoothing scheme to divide the image into two regions.…”