An Efficient Denoising Algorithm for Impulse Noise Removal

A Rajamani,V Krishnaveni

doi:10.3844/jcssp.2015.57.63

Abstract

Now-a-days the images acquired by the digital cameras and defective sensors tend to introduce noises during either image acquisition or transmission process. The quality of the image is degraded in a significant measure. Lot of research works was carried out for several decades to denoise the impulse noise and each approach has its own merits and demerits. This study deals with a new denoising approach for the gray scale images to discard fixed type salt and pepper noise present in the images. This algorithm was implemented for gray scale images such as Lena and cameraman and the performance results are really challenging both qualitative and quantitative wise. This study considered the performance metrics like PSNR and MSE for quantitative measure and presents better results for low density noise level to high density noise level (up to 100%), when compared to other existing filters. The visual interpretation shows that this method proves better in qualitative analysis by human perception too. In addition to this the proposed approach decreases the computational and hardware complexity by an appreciable manner since traditional sorting schemes does many comparisons and that were very much avoided. Thus very fast operation could be achieved. This study deals with neighborhood pixel comparison which are confined to previous pixel and the pixel next to the processing pixel under consideration, the absence of sorting saves much time and number of operations, which in turn speed of operation is increased and better reconstruction of images is achieved.

Highlights

The digital images which are taken by a camera system yields noises during image acquisition or transmission, due to the reasons such as the out of focus of the picture due to motion of camera, troublesome weather, atmospheric turbulence, sensor problem, storage of information and noise during digital conversion process such as sampling and quantization
The proposed algorithm results are presented in terms of qualitative and quantitative wise and a comparative study was done among other algorithms such as Decision Based Algorithm (DBA) (Zhang et al, 2013)
The proposed algorithm has been compared with the other competitive algorithms such as Standard Median Filter (SMF), Adaptive Median Filter (AMF), PSMF, WMF, TDF, LDS, DBA, MDBA, Modified Decision Based Unsymmetric Trimmed Median Filter (MDBUTMF) and MAUTMPF

Summary

Introduction

The digital images which are taken by a camera system yields noises during image acquisition or transmission, due to the reasons such as the out of focus of the picture due to motion of camera, troublesome weather, atmospheric turbulence, sensor problem, storage of information and noise during digital conversion process such as sampling and quantization. It is mandatory to remove those noises which make it difficult to interpret the image for further processing. There are various types of noises that will affect an image’s quality namely Gaussian noise, salt and pepper noise, random noise (Dong and Xu, 2007), speckle noise, to name a few. Each type of noise is defined by its own characteristic features and removal of these noise components from the image is performed by various ways. Some of the noises due to transmission are mainly affected by (salt and pepper) which is additive in nature. Denoising is essential for visually pleasant images by improving image quality and will be helpful for other postprocessing operations like segmentation and registration

Results

Discussion

Conclusion