Hanying Zheng | Searcharxiv

arXiv2020

NAMF: A Non-local Adaptive Mean Filter for Salt-and-Pepper Noise Removal

In this paper, a novel algorithm called a non-local adaptive mean filter (NAMF) for removing salt-and-pepper (SAP) noise from corrupted images is presented. We employ an efficient window detector with adaptive size to detect the noise, the noisy pixel will be replaced by the combination of its neighboring pixels, and finally we use a SAP noise based non-local mean filter to reconstruct the intensity values of noisy pixels. Extensive experimental results demonstrate that NAMF can obtain better performance in terms of quality for restoring images at all levels of SAP noise.

cs.CV↗

arXiv2020

A novel centroid update approach for clustering-based superpixel methods and superpixel-based edge detection

Superpixel is widely used in image processing. And among the methods for superpixel generation, clustering-based methods have a high speed and a good performance at the same time. However, most clustering-based superpixel methods are sensitive to noise. To solve these problems, in this paper, we first analyze the features of noise. Then according to the statistical features of noise, we propose a novel centroid update approach to enhance the robustness of clustering-based superpixel methods. Besides, we propose a novel superpixel-based edge detection method. The experiments on BSD500 dataset show that our approach can significantly enhance the performance of clustering-based superpixel methods in noisy environment. Moreover, we also show that our proposed edge detection method outperforms other classical methods.

cs.CV↗