In recent world video and image compression, enhancement, restoration have become very essential. There are many applications where we need to use different transform techniques to convert the signal or data in frequency or time domain. However, with the wide spread of image usage in many fields of our lives, it becomes very important to develop new techniques. The previous research was based on Discrete wavelet transform. In this paper, we introduce Dual tree Complex Wavelet Transform and Double Density Complex Wavelet Transform for applications such as image restoration and enhancement. This introduces limited redundancy (4:1 for 2-dimensional signals) and allows the transform to provide approximate shift invariance and directionally selective filters (properties lacking in the traditional wavelet transform) while preserving the usual properties of perfect reconstruction and computational efficiency. We show how the dual-tree complex wavelet transform and Double Density complex wavelet transform can provide a good basis for multiresolution image denoising and de-blurring.
compression, double density complex wavelet transform, invariance, multiresolution, redundancy
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