Multilevel thresholding is a popular image segmentation technique. However, computational complexity of multilevel … thresholding increases very rapidly with increasing number of thresholds. Metaheuristic algorithms are applied to reduce … computational complexity of multilevel thresholding. A new method of multilevel thresholding based on Moth-Flame Optimization (MFO …

filter is usually used to enhance the blood vessels. The enhancement filter is designed from the adaptive thresholding of the …

thresholding approach is proposed for better image denoising. The performance of the proposed work is compared with some edge …

We study the distribution of hard-, soft-, and adaptive soft-thresholding estimators within a linear regression model …

the Principal Orthogonal complEment Thresholding (POET) method to explore such an approximate factor structure. The POET … estimator includes the sample covariance matrix, the factor-based covariance matrix (Fan, Fan and Lv, 2008), the thresholding … estimator (Bickel and Levina, 2008) and the adaptive thresholding estimator (Cai and Liu, 2011) as specic examples. We provide …

processing techniques and neural networks. Image processing techniques like thresholding, filtering, edge detection …

and Adaptive Median filters are compared using Mean Squared Error and Peak Signal-to-Noise Ratio. Otsu's thresholding is …