Author(s): M.Vijay | L.Saranya Devi
Journal: International Journal of Soft Computing & Engineering
ISSN 2231-2307
Volume: 2;
Issue: 1;
Start page: 411;
Date: 2012;
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Keywords: Image Denoising | Joint Bilateral Filter | Multiscale LMMSE | Interscale Wavelet Model.
ABSTRACT
This paper deals with LMMSE-based denoising scheme with a wavelet interscale model and Joint bilateral Filter in spatial domain. The proposed algorithm consists of two stages .In the first stage, a vector is represented by the wavelet coefficients at the same spatial locations at two adjacent scales and the LMMSE is applied to the vector. Compare to Orthogonal Wavelet Transform (OWT), Overcomplete Wavelet Expansion (OWE) provides better results hence it is employed. While applying the LMMSE rule, the important features in an image like edges, curves and textures can be identified. Also spatial domain method output provides a high quality denoising image than wavelet method with fewer artifacts; hence this wavelet domain output as a reference image for the Joint Bilateral Filter (JBF) .By using this reference image and the non-linear combination of information of adjacent pixel, the edge details of the images can be preserved in a well manner. The experimental results prove that the proposed approach is competitive when compared to other denoising methods in reducing various types of noise. Also the proposed algorithm outperforms other methods both visually and in case of objective quality peak-signal-to-noise ratio (PSNR).
Journal: International Journal of Soft Computing & Engineering
ISSN 2231-2307
Volume: 2;
Issue: 1;
Start page: 411;
Date: 2012;
VIEW PDF
DOWNLOAD PDF Original pageKeywords: Image Denoising | Joint Bilateral Filter | Multiscale LMMSE | Interscale Wavelet Model.
ABSTRACT
This paper deals with LMMSE-based denoising scheme with a wavelet interscale model and Joint bilateral Filter in spatial domain. The proposed algorithm consists of two stages .In the first stage, a vector is represented by the wavelet coefficients at the same spatial locations at two adjacent scales and the LMMSE is applied to the vector. Compare to Orthogonal Wavelet Transform (OWT), Overcomplete Wavelet Expansion (OWE) provides better results hence it is employed. While applying the LMMSE rule, the important features in an image like edges, curves and textures can be identified. Also spatial domain method output provides a high quality denoising image than wavelet method with fewer artifacts; hence this wavelet domain output as a reference image for the Joint Bilateral Filter (JBF) .By using this reference image and the non-linear combination of information of adjacent pixel, the edge details of the images can be preserved in a well manner. The experimental results prove that the proposed approach is competitive when compared to other denoising methods in reducing various types of noise. Also the proposed algorithm outperforms other methods both visually and in case of objective quality peak-signal-to-noise ratio (PSNR).