Research Article Open Access

Comparative Analysis of Satellite Image Pre-Processing Techniques

T. Sree Sharmila1, K. Ramar2 and T. SreeRenga Raja3
  • 1 SSN College of Engineering, India
  • 2 Einstein College of Engineering, India
  • 3 Anna University, India

Abstract

Satellite images are corrupted by noise in its acquisition and transmission. The removal of noise from the image by attenuating the high frequency image components, removes some important details as well. In order to retain the useful information and improve the visual appearance, an effective denoising and resolution enhancement techniques are required. In this research, Hybrid Directional Lifting (HDL) technique is proposed to retain the important details of the image and improve the visual appearance. The Discrete Wavelet Transform (DWT) based interpolation technique is developed for enhancing the resolution of the denoised image. The performance of the proposed techniques are tested by Land Remote-Sensing Satellite (LANDSAT) images, using the quantitative performance measure, Peak Signal to Noise Ratio (PSNR) and computation time to show the significance of the proposed techniques. The PSNR of the HDL technique increases 1.02 dB compared to the standard denoising technique and the DWT based interpolation technique increases 3.94 dB. From the experimental results it reveals that newly developed image denoising and resolution enhancement techniques improve the image visual quality with rich textures.

Journal of Computer Science
Volume 9 No. 2, 2013, 176-182

DOI: https://doi.org/10.3844/jcssp.2013.176.182

Submitted On: 29 May 2012 Published On: 1 April 2013

How to Cite: Sharmila, T. S., Ramar, K. & Raja, T. S. (2013). Comparative Analysis of Satellite Image Pre-Processing Techniques. Journal of Computer Science, 9(2), 176-182. https://doi.org/10.3844/jcssp.2013.176.182

  • 2,949 Views
  • 3,442 Downloads
  • 10 Citations

Download

Keywords

  • Denoising
  • Discrete Wavelet Transform
  • Enhancement
  • Hybrid Directional Lifting
  • Peak Signal to Noise Ratio