Improvement of linear filter in image denoising

Lingshuai Kong; Hongyan Wen; Lei Guo; Qingtao Wang; Yakun Han

doi:10.1117/12.2207241

9 December 2015 Improvement of linear filter in image denoising

Lingshuai Kong, Hongyan Wen, Lei Guo, Qingtao Wang, Yakun Han

Proceedings Volume 9808, International Conference on Intelligent Earth Observing and Applications 2015; 98083F (2015) https://doi.org/10.1117/12.2207241
Event: International Conference on Intelligent Earth Observing and Applications, 2015, Guilin, China

Abstract

Image noise is one of important factors that affects quality of image in the process of remote sensing imaging. So. the image de-noising is a basic and key technology in the field of image processing. In this paper, the classical linear filtering, such as arithmetic average filter, harmonic mean filter, and geometric mean filter , are applied to do the image de-noising and the analysis for the characteristics of each de-noising method. The improvement scheme of the linear filtering which based on the mean filtering is proposed by the way of adding the threshold, and the root mean square error (MSE) and peak signal to noise ratio (PSNR) are used on its accuracy evaluation.

Citation Download Citation

Lingshuai Kong, Hongyan Wen, Lei Guo, Qingtao Wang, and Yakun Han "Improvement of linear filter in image denoising", Proc. SPIE 9808, International Conference on Intelligent Earth Observing and Applications 2015, 98083F (9 December 2015); https://doi.org/10.1117/12.2207241

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available