Abstract
Digital Image Processing initial step always starts with Image acquisition which is a start point for further analysis. Generally an analysis of skin lesion images is performed offline which increases the chances of having more disturbances in terms of noise, artifacts or air bubbles. Noise is one of the disturbing elements of this image acquisition which can lead to incorrect segmentation, analysis, or classification. In this paper, a new method Dmey Wavelet Gaussian Filter (DWGF) have been proposed for removing Gaussian type of noise based on Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR) performance measures. Wavelet transformation filters, Low pass filters and proposed (DWGF) method have been tested on large data set of skin lesion images through quality measures in which low MSE (91.9083) and high PSNR (28.5313) proves to be better in DWGF. This method can be used for further analysis and detection of various skin diseases in Computer Aided Diagnostic System.
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Arora, G., Dubey, A.K., Jaffery, Z.A. (2019). Design of Dmey Wavelet Gaussian Filter (DWGF) for De-noising of Skin Lesion Images. In: Tiwari, S., Trivedi, M., Mishra, K., Misra, A., Kumar, K. (eds) Smart Innovations in Communication and Computational Sciences. Advances in Intelligent Systems and Computing, vol 851. Springer, Singapore. https://doi.org/10.1007/978-981-13-2414-7_44
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DOI: https://doi.org/10.1007/978-981-13-2414-7_44
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