Brightness and Resolution Enhancement of Satellite Images using SVD and DWT

Ammu Anna Mathew; S. Kamatchi

doi:https://doi.org/10.14445/22315381/IJETT-V4I4P241

Research Article | Open Access | Download PDF

Volume 4 | Issue 4 | Year 2013 | Article Id. IJETT-V4I4P241 | DOI : https://doi.org/10.14445/22315381/IJETT-V4I4P241

Brightness and Resolution Enhancement of Satellite Images using SVD and DWT

Ammu Anna Mathew , S. Kamatchi

Citation :

Ammu Anna Mathew , S. Kamatchi, "Brightness and Resolution Enhancement of Satellite Images using SVD and DWT," International Journal of Engineering Trends and Technology (IJETT), vol. 4, no. 4, pp. 712-718, 2013. Crossref, https://doi.org/10.14445/22315381/IJETT-V4I4P241

Abstract

A new satellite image resolution and brightness enhancement technique based on the discrete wavelet transform (DWT) and singu lar value decomposition (SVD) has been proposed. Satellite images are used in many applications such as geosciences studies, astronomy, and geographical information systems. One of the most important quality factors in images comes from its resolution. The technique decomposes the input image into the four frequency sub - bands by using DWT and estimates the singular value matrix of the low – low sub band image, and, then, it reconstructs the enhanced image by applying inverse DWT. The technique also estimates the singular value matrix of the low – low sub band of histogram equalized image and normalize both singular value matrices to obtain brightness enhanced image. The technique is compared with conventional image equalization techniques such as standard gener al histogram equalization and local histogram equalization, as well as state - of - the - art techniques such as brightness preserving dynamic histogram equalization and singular value equalization. The experimental results show the superiority of the proposed m ethod over conventional and state - of - the - art technique.

Keywords

Fault Detection, Parameter Estimation, Recursive Least Squares, Fast Least Squares, Statistical Control Chart

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