Indian Journal of Science and Technology
DOI: 10.17485/ijst/2015/v8i24/80153
Year: 2015, Volume: 8, Issue: 24, Pages: 1-6
Original Article
V. Sowmya* , Neethu Mohan and K. P. Soman
Centre for Excellence in Computational Engineering and Networking, Amrita Vishwa Vidyapeetham, Amrita Nagar, Coimbatore – 641112, Tamil Nadu, India;
[email protected], [email protected], [email protected]
Noise is one of the prime factors which degrade the quality of an image. Hence, image denoising is an essential image enhancement technique in the image processing domain. In this paper, we use low-pass sparse banded filter matrices for image denoising. Sparsity is the key concept in this filter design. We applied the designed low-pass filter both row-wise and column-wise to denoise the image. The proposed method is experimented on standard test images corrupted with different types of noises namely Gaussian, White Gaussian, Salt & Pepper and Speckle with noise level equals to 0.01, 0.05 and 0.1. The effectiveness of the proposed method of denoising is evaluated by the computation of standard quality metric known as Peak Signal-to-Noise Ratio (PSNR). The experimental result analysis shows that the proposed image denoising technique based on sparse banded filter matrices results in significant improvement in PSNR around 2dB to 8dB for a different type of noises with noise level equal to 0.1 and is also aided by the visual analysis.
Keywords: Image Denoising, Low-pass Filter, Noise, Sparse Banded Filter.
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