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Performance Improvement in Noise Reduction Based On Double Density Dual Tree Complex Wavelet Transform
Abstract
In the image de-noising process two types of techniques are there- named (a) Dual-tree Complex Wavelet Transform (DTCWT) and (b) Double Density Dual Tree Complex Wavelet Transform (DDDTCWT). In this paper, the noise in the image is reduced using the technique the Double Density Dual Tree Discrete Wavelet Transform technique with directive noise samples of input. By comparing the Dual-Tree and Double Density Dual Tree Discrete Wavelet Transform techniques, the DDDTDWT technique has more directionality than DTCWT. During the de-noising process, Soft threshold and shrinkage are used to reduce the noise. DDDTDWT exhibits better performance with improved PSNR (Peak Signal-to-Noise Ratio) values by considering the known noise samples from input image instead of the unknown noise estimation.
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References
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