Moran’s I for impulse noise detection and removal in color images
Chih‐Cheng Hung, Eun Suk Chang · Journal of Electronic Imaging · 2017
An approach for impulse noise detection and removal in color images based on Moran’s I (MI) statistic is proposed. The proposed method consists of detection and removal components and is called Moran’s I vector median filter (MIVMF). The detection module is able to determine if a pixel is noise or noise-free. If it is a noise pixel, the vector median filter (VMF) will be used to remove the noise. This detection capability meets the so-called “switching” mechanism, which only selects noisy pixels for denoising. Hence, this proposed filter will expedite the processing time with the reduced number of vector calculations in the VMF due to this detection function. This type of detection is achieved with MI index and the indication of one-dimensional Laplacian kernels. We compare the proposed MIVMF with other well-developed vector-type median filters in the literature. Our experimental results show that the proposed filter is not only faster in the filtering process but also efficient in removing random impulse noise with different noise levels in color images. The MIVMF demonstrates a promising denoising result based on the criteria of peak signal-to-noise ratio and structural similarity index metric. With the visualization of processed images, the MIVMF can avoid image blurring, preserve the edge details, and achieve superior noise reduction.