Novel Method of Color Image Enhancement Based on Daubechies D4 Wavelet Analysis

Murtaza Saadique Basha, Dr.M. Ramakrishnan


Wavelet transform is an important mathematical tool with strong application in signal processing. From the mathematical point of view,
many different wavelet transforms are developed, where orthogonal wavelet transforms are more important. The main idea is to transform filter
characteristics to wavelet Daubechies D4 representation before ANN training. The technique used is a new methodology to a multi-resolution digital
signal analysis by discrete wavelet transforms. Our proposed method is to implement approximation digital signal scheme using Daubechies D4
wavelets. The present technique exhibits a revised procedure of removing distortion (loss) generated from the approximated double length digital
signal presented in. For highly nonlinear digital signal, the technique fails to approximate the signal but the proposed revised technique can
approximate the signal. At the beginning, a short mathematical introduction of the Daubechies D4 transform is presented. The proposed method not
only enables approximating digital signals in a better way but also it approximates highly nonlinear digital signals. Texture patterns from seed clone
images are then analyzed through wavelet's Daubechies D4 algorithm which produces discrete frequency coefficients representing the extracted
features. Previous work only utilized three statistical parameters representing these coefficients such as mean, variance and standard deviation as the
inputs for designing an intelligent identification model for various rubber tree seed clones.

Keywords: Discrete Wavelet Transform (DWT), Digital watermarks, D4wavelet transforms, color space, histogram equalization, Spatial Domain

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