DWT and PCA Based Image Enhancement with Gaussian Filter
R. Vani1, K. Soundara Rajan2
1R.Vani, Research Scholar / J.N.T.U.A.C.E.A, Anantapur, Andhra Pradesh, India.
2K.Soundara Rajan, M.Tech. PhD / J.N.T.U.A.C.E.A, Anantapur, Andhra Pradesh, India.
Manuscript received on February 05, 2013. | Revised Manuscript received on February 09, 2013. | Manuscript published on February 15, 2013. | PP: 45-47 | Volume-1 Issue-3, February 2013 . | Retrieval Number: B0125011213/2013©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: A new satellite image contrast enhancement technique based on the Discrete Wavelet Transform (DWT) and Principal Component Analysis has been proposed. By the use of discrete wavelet transform, the input image decomposed into four frequency sub-bands and estimates the eigen values and eigen vectors (PCA) of the low–low subband image and reconstructs the enhanced image by applying inverse DWT. The technique is compared with conventional image equalization techniques such as standard general histogram equalization and local histogram equalization, as well as state-of-the-art techniques such as brightness preserving dynamic histogram equalization and Principal Component Analysis. The experimental results show the superiority of the proposed method over conventional and state-of-the-art techniques.
Keywords: Discrete wavelet transform, image equalization, satellite image Contrast enhancement.