Selection of the best wavelet from various wavelet families for image compression is challenging problem. There are many wavelets that can be used to transform an image in a wavelet-based codec. However, it is necessary to use only 'one' wavelet to compress an image. The most appropriate wavelet will give a good compressed image; otherwise the wrong selection will produce a low quality image. This paper applies artificial neural network (ANN) as a method to solve this problem instead of manual selection as in a conventional wavelet-based codec. The results show that the neural network based on image characteristics can be used as a solution to solve the problem. The input variables to the ANN are two image features, namely image gradient (IAM) and spatial frequency (SF) from three colour components (red, green and blue) and the output the ANN is the wavelet type.
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