Abstract
The aim of this paper is to investigate how we can make use of Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) in image sharpening to enhance image quality. The fundamental idea of image sharpening is to make use of image edges or high frequency components to bring out invisible details. Both DWT and DCT can be used to isolate the high frequency components of the original image as they are able to separate the frequency components into high and low portions. An analysis of the results suggests that DWT is more suited to the task. Focusing on DWT, we propose a wavelet-based algorithm for image sharpening. In this algorithm, an image containing the edge information of the original image is obtained from a selected set of wavelet coefficients. This image is then combined with the original image to generate a new image with enhanced visual quality. An effective approach is designed to remove those coefficients related with noise rather than the real image to further enhance the image quality. Experimental results demonstrate the effectiveness of the proposed algorithm for image sharpening purpose.
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Liu, Y., Toh, Y.H., Ng, T.M., Liew, B.K. (2009). Study on Transform-Based Image Sharpening. In: Lee, R., Hu, G., Miao, H. (eds) Computer and Information Science 2009. Studies in Computational Intelligence, vol 208. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01209-9_13
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DOI: https://doi.org/10.1007/978-3-642-01209-9_13
Publisher Name: Springer, Berlin, Heidelberg
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