• B.Vasantha Lakshmi
• Dr.D.Elizabath Rani

Current research is going on to detect the skin cancer from skin lesions using image processing methods. The skin cancer detection involves two basic steps namely, image de-noising and image segmentation. In any image, de-noising is important because image quality is degraded by noise. The process of filtering the noise is de-noising. This paper proposes a novel approach for de-noising of skin cancer images, which is performed using Bi- orthogonal wavelet, transform at different levels of decomposition. Adaptive thresholding method is implemented on noisy image, by adding Salt & Pepper noise to the actual image. The performance of the proposed method is evaluated using statistical performance metrics, like arithmetic mean, median, standard deviation, L1norm, L2norm and maxi norm.

De-noising, wavelet transform, Adaptive thresholding, statistical performance metrics, standard deviation.

"De-noising of Skin Cancer Images Using Wavelet Thresholding and Analysis of Statistical Performance Metrics", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.128-131, May 2019, Available :http://www.jetir.org/papers/JETIRCY06020.pdf

"De-noising of Skin Cancer Images Using Wavelet Thresholding and Analysis of Statistical Performance Metrics", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp128-131, May 2019, Available at : http://www.jetir.org/papers/JETIRCY06020.pdf