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Efficient analysis of hybrid directional lifting technique for satellite image denoising

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Abstract

Satellite images are often corrupted by noise in the acquisition and transmission process. While removing noise from the image by attenuating the high frequency image components, it removes some important details as well. In order to improve the visual appearance and retain the useful information of the images, an effective denoising technique is required to reduce the noise level. For denoising, many researches exploit the directional correlation in either spatial or frequency domain. However, the orientation estimation for directional correlation becomes inefficient and error prone in noised circumstances. This paper proposes a new hybrid directional lifting (HDL) technique for image denoising that involves pixel classification and orientation estimation, along with adding small amount of noise, in order to improve the performance efficiency of the technique. Experimental results show that the HDL technique improves both peak signal to noise ratio and visual quality of images with rich textures.

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Abbreviations

I(i, j):

Input image

V var(i, j):

Variance of the local window centered by the pixel

V n :

Variance of the noisy image

T :

Threshold value

flag(i, j) = 0:

Label for smooth region

flag(i, j) = 1:

Label for texture region

D x , D y :

Gradient factors

row, col:

Size of an image

D xnew, D ynew :

New convolution matrices

dir(i, j):

Directional information of each pixel

tan−1 :

Inverse of the tangent function

dirnew(i, j):

Modified direction of each pixel

p(x/ROI):

Conditional probability distribution function of ROI

p(x/RONI):

Conditional probability distribution function of RONI

dirmin(i, j):

Minimum direction estimation of each pixel

H(i, j):

Hybrid transform

R(i, j):

Small random value matrix

D(i, j):

Denoised image

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Authors and Affiliations

  1. Department of Information Technology, SSN College of Engineering, Chennai, 603 110, Tamilnadu, India

    T. Sree Sharmila

  2. Department of Computer Science and Engineering, Einstein College of Engineering, Tirunelveli, 627 012, Tamilnadu, India

    K. Ramar

Authors
  1. T. Sree Sharmila
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  2. K. Ramar
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Correspondence to T. Sree Sharmila.

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Sree Sharmila, T., Ramar, K. Efficient analysis of hybrid directional lifting technique for satellite image denoising. SIViP 8, 1399–1404 (2014). https://doi.org/10.1007/s11760-012-0369-2

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  • DOI: https://doi.org/10.1007/s11760-012-0369-2

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