Salt and Pepper Noise Estimation and Removal Techniques and its Performance Evaluation

Apoorwa Tiwari*, Devanand Bhonsle**
* PG Scholar, Department of Electronics and Telecommunication Engineering, SSTC-SSGI, Faculty of Engineering & Technology, Bhilai, Chhattisgarh, India.
** Senior Assistant Professor, Electrical and Electronics Engineering, SSTC-SSGI, Faculty of Engineering & Technology, Bhilai, Chhattisgarh, India.
Periodicity:December - February'2017
DOI : https://doi.org/10.26634/jpr.3.4.13541

Abstract

Visual data transmitted in the form of a digital image is becoming a major method for visual communication in today's era, but the image obtained after the transmission is often corrupted with many types of noise. Noise is an important factor which, when get added to an image, reduces the quality and appearance. So in order to enhance the image quality, it must be removed with preserving the textural information and structural features of image. There are different types of noises exist which corrupts the images. Selection of the de-noising algorithm is application oriented [17]. Here in this paper, two filters were used; one is trim median filter used for estimation and removal of noise from image corrupted with Salt and Pepper and the other filter is Gaussian filter which is used for Gaussian noise estimation and reduction [16]. This is clearly a better algorithm because it is based on a modified decision based system. In this paper, the authors propose a modified decision based modified trim median filter algorithm for the restoration and effective suppression of gray scale and the color images that are highly corrupted by salt and pepper noise. The authors also calculate the presence of Gaussian noise in any noisy digital images. The authors implement a GUI for estimating the density of saltpepper noise in degraded images using joint entropy value and mutual information. The joint entropy value between the noisy image and the original image or other typical images was introduced in this paper to depict the inter-correlation.

The system is tested against the different color and grayscale images and its gives the better [2] Peak Signal-to-Noise Ratio (PSNR) and Image Enhancement Factor (IEF).

Keywords

Gaussian Noise, Salt and Pepper Noise, Trimmed Median Filter, Noise Estimation, Peak Signal-to-Noise Ratio (PSNR), Image Enhancement Factor (IEF), Noise Estimation, Trimmed Filter

How to Cite this Article?

Tiwari, A., and Bhonsle, D. (2017). Salt and Pepper Noise Estimation and Removal Techniques and its Performance Evaluation. i-manager’s Journal on Pattern Recognition, 3(4), 28-34. https://doi.org/10.26634/jpr.3.4.13541

References

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