Wavelet Image Denoising Based on the New Threshold Function

Abstract

A new threshold function was proposed to overcome that hard threshold function is not continuous, soft threshold function has constant deviation and derivative discontinuity defects. It will be applied to using different thresholds denoising method with different decomposition level based on the D.J global threshold. Experimental results shows that the denoising result of new threshold function is superior to the traditional soft and hard threshold function in minimum mean square error (MSE) and peak signal to noise ratio (PSNR).

Use The Coiflets and Daubechies Wavelet Transform To Reduce Data Noise For a Simple Experiment

“…And It is considered one of the standard techniques for processing observational noise (Tang et al, 2013) (Han & Xu, 2016).…”

“…Then the characteristics of the field yield were taken, which are (number of branches, plant height cm, dry weight of g, number of spikes / m 2 , number of seeds/spike, weight of 1000 grains of/ g, Grain yield / m²), where the trait was studied: grain yield / m 2 . By applying equations (10)(11)(12)(13)(14)(15)(16)(17)(18)(19)) on experiment observations, The results are shown in table (1), Which represents a summary of wavelet transformation when the level of analysis is (J-4)…”

“…By applying equations (10)(11)(12)(13)(14)(15)(16)(17)(18)(19)) on experiment observations, The results are shown in table (2), Which represents a summary of wavelet transformation when the level of analysis is (J-5)…”