Abstract

Determination of the threshold value is extremely an important part in wavelet based image de-noising. Finding appropriate threshold value can be done either by using deterministic approaches or soft computing algorithms. Artificial Bee Colony (ABC) is one of the algorithms motivated by the intelligent behaviour of honey bees. In this paper, a nature inspired population based image de-noising technique has been implemented to find the dynamic threshold value using an ABC algorithm by using Dual Tree Complex Wavelet Transform (DT-CWT). The DT-CWT is a relatively recent enhancement to the Discrete Wavelet Transform (DWT) with two additional properties known as shift invariance and directional selectivity. These additional features are in turn used to preserve geometric image features like ridges and edges. The performance of the proposed method has been compared in terms of Peak Signal to Noise Ratio (PSNR) with conventional wavelet thresholding using DT-CWT and Adaptive Median Filter (AMF) techniques.

Keywords
Keywords: Image De-noising, Dual Tree Complex Wavelet Transform, Artificial Bee Colony Optimization, Peak Signal-to- Noise Ratio.

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