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Computational Research Progress in Applied Science and Engineering

CRPASE 2017, 3(3), 104-108

Translation Invariant Wavelet Based Noise Reduction Using a New Smooth Nonlinear Improved Thresholding Function

Authors

Noorbakhsh Amiri Golilarz 1*, Niyifasha Robert 2, Jalil Addeh 3, Amin Salehpour 1

ABSTRACT

In this paper, a new type of thresholding function is introduced for wavelet based image de-noising. Here we combined the new smooth nonlinear improved thresholding function with translation invariant wavelet transform (TIWT). Unlike the common thresholding functions (hard and soft thresholding), the new proposed function is smooth and nonlinear. Applying this thresholding function on wavelet transform provides us with better resolution and higher peak signal to noise ratio (PSNR) in comparison with some other available techniques in image de-noising. The proposed method achieves up to 2.45 dB improvement over the state-of-the-art for de-noising ‘Boat’ image.

Image de-noising; Improved thresholding function; Translation invariant wavelet transform; Noise reduction.
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