Speckle Noise Removal and Enhancement of SAR Images
Saumya Dubey1, Deepak Tiwari2, O.P.Singh3, K.K. Singh4
1Saumya Dubey, Dept of Electronics and Communication Engineering, Amity University, of Technology, Uttar Pradesh, Lucknow Campus, India.
2Deepak Tiwari, Dept of Electronics and Communication Engineering, Amity University, of Technology, Uttar Pradesh, Lucknow Campus, India.
3Dr. O P Singh, Dept of Electronics and Communication Engineering, Amity University, of Technology, Uttar Pradesh, Lucknow Campus, India.
4K K Singh, Astt. Prof, Dept of Electronics and Communication Engineering, Amity University, of Technology, Uttar Pradesh, Lucknow Campus, India.
Manuscript received on March 12, 2013. | Revised Manuscript received on April 13, 2013. | Manuscript published on April 30, 2013. | PP: 639-644| Volume-2, Issue-4, April 2013. | Retrieval Number: D1548042413/2013©BEIESP
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© The Authors. 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: Synthetic Aperture Radar (SAR) images are mostly corrupted by speckle noise and this type of noiseis produced due to the coherent nature of scattering phenomenon, so the removal of speckle noise from the SAR images without the loss of structural features and textural information becomes very necessary. This paper presents the de-noising of SAR image and enhancement techniques for providing good visual quality to the SAR images. Here the wavelet thresholding technique is applied to noisy SAR image then Contrast Enhancement Techniques and finally morphological operation is implemented on de-noised SAR image. In this paper the implementation of de-noising technique with the enhancement techniques as a whole is the proposed method. The experimental results show the proposed method outperforms. The tabulated results of all techniques are shown in terms of Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE) parameters. The proposed approach provides better visualization effectiveness and improvement in both parameter values. All the simulation is done with the help of MATLAB R2010a environment.
Keywords: SAR, DWT, Contrast Enhancement, Morphological Operation, PSNR, MSE.