Efficient Star Shaped Search Pattern Based Image De-noising

Abstract

The investigation for well-organized picture De-blurring techniques are still valid challenge, because of their complexities in functional analysis and statistics. In this research, a series of salt-and-pepper (SAP) noise reduction method based on star shaped search pattern that can be applicable for monochrome images is presented. A great benefit of the proposed De-blurring is robotical detection of noise position based on star shaped search pattern and replacement of noisy pixels. The proposed De-blurring is also named as star shaped search pattern-salt & pepper- image de-noising (SSSP-SP-ID). The SSSP-SP-ID system is customizable and furthermore it is easy and fast. The investigation shows that the SSSP-SP-ID De-blurring algorithm have better outcomes compared to other state-of-the-art algorithms, when the noise density (ND) is moderate or high. The performance of SSSP-SP-ID De-blurring algorithm is measured using quantitative performance measures such as peak signal-to-noise ratio (PSNR), structure similarity index measure (SSIM) and image enhancement factor (IEF).