Abstract
In this paper, a novel X-ray image contrast enhancement method using the second generation curvelet transform is proposed in order to better enhance contrast and edges while remove noise. First, source images are decomposed in the curvelet transform domain. A nonlinear enhancement operator is applied to low frequency subbands to enhance global contrast. Combining with threshold denoising, the nonlinear enhancement operator is also applied to high frequency subbands to enhance edges and reduce noise. Finally, the processed coefficients are reconstructed to obtain enhanced images. Experimental results on X-ray images show that compared with histogram equalization and wavelet based contrast enhancement, the proposed method can effectively enhance contrast and edges of X-ray images while better reducing noise, thus has better visual effect.
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Li, H., Huo, G. (2012). X-ray Image Contrast Enhancement Using the Second Generation Curvelet Transform. In: Huang, DS., Jiang, C., Bevilacqua, V., Figueroa, J.C. (eds) Intelligent Computing Technology. ICIC 2012. Lecture Notes in Computer Science, vol 7389. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31588-6_46
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DOI: https://doi.org/10.1007/978-3-642-31588-6_46
Publisher Name: Springer, Berlin, Heidelberg
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