An Efficient Image Denoising Method based on Bilateral filter Model and Neighshrink SURE
Mukund N Naragund1, Basavaraj N Jagadale2, Priya B S3, Panchaxri4, Vijayalaxmi Hegde5
1Mukund N Naragund, Department of Physics and Electronics, CHRIST (Deemed to be University), Bengaluru, India.
2Basavaraj N Jagadale, Department of PG studies and research in Electronics, Kuvempu University, Shimoga, India.
3Priya B S, Department of Electronics, Kuvempu University, Shimoga, India.
4Panchaxri, Department of Electronics, SSA Govt. First grade College, Ballari , India.
5Vijayalaxmi Hegde, Department of Electronics, MESMM Arts and Science College, Sirsi, India.
Manuscript received on 02 August 2019. | Revised Manuscript received on 07 August 2019. | Manuscript published on 30 September 2019. | PP: 8470-8475 | Volume-8 Issue-3 September 2019 | Retrieval Number: C6629098319/2019©BEIESP | DOI: 10.35940/ijrte.C6629.098319
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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: In all the instances of image acquisition, transmission and storage, the unwanted noise gets into the information content of the image and thereby introduces an unpleasant visual quality to the observer. So the field of image processing has produced a lot of image denoising algorithms and techniques to improve the visual quality of the image. Since noise cannot be reduced to zero practically, the need for faithful and efficient denoising techniques to produce almost noiseless images demands a systematic research work in the field of denoising methods. The denoising process using a bilateral filter even though produces improvement in the image quality, it does not show consistency when the noise level is high and also the peak signal to noise ratio (PSNR) and Image quality Index (IQI) do not show any improvement. This paper proposes an improved algorithm that incorporates the function of bilateral filter model and wavelet thresholding using Neighshrink SURE method. The results show significant improvement in both PSNR and IQI values with respect to the four standard test images under various noise conditions.
Keywords: Image Denoising, Bilateral Filter, Wavelet Thresholding, Neighshrink SURE.
Scope of the Article: Image Processing and Pattern Recognition