Noise reduction based on Double Density Discrete Wavelet Transform

The wavelet transform is a well-known tool that can be used for many signal processing applications. This paper investigates the success of Double Density Discrete Wavelet Transform (DDDWT) to denoise the signals and images. The performance analysis of one dimensional signal and two dimensional images are compared with discrete wavelet transform (DWT). The Double Density DWT has an one scaling function and two wavelet functions. With these two wavelets gives a closer spacing between adjacent wavelets within the same scale. It is found that with same level of processing, the double density DWT (DDDWT) performs better than DWT.