Many thresholding-based image enhancement techniques have been developed and used for document analysis, where the simplicity and efficiency of thresholding makes it ideal to use for classifying layers within documents. However, the efficiency of these enhancement techniques can be impaired by the variation of grey levels in different documents, thus causing over-thresholding or under-threshold...

In this paper, Discrete-wavelet transform (DWT) based algorithm are used for speech signal denoising. Here both hard and soft thresholding are used for denoising. Analysis is done on noisy speech signal corrupted by babble noise at 0dB, 5dB, 10dB and 15dB SNR levels. Simulation & results are performed in MATLAB 7.10.0 (R2010a). Output SNR (Signal to Noise Ratio) and MSE (Mean Square Error) is c...

Image thresholding and edge detection are crucial in image processing and understanding. In this chapter, the authors propose a hierarchical multilevel image thresholding method for edge information extraction based on the maximum fuzzy entropy principle. In order to realize multilevel thresholding, a tree structure is used to express the histogram of an image. In each level of the tree structu...

In this article we investigate the asymptotic and numerical properties of a class of block thresholding estimators for wavelet regression. We consider the effect of block size on global and local adaptivity and the ch oice of thresholding constant. The optimal rate of convergence for block thresholding with a given block size is derived for both the global and local estimation. It is shown that...

Segmentation is one of the essential tasks in image processing. Thresholding is one of the simplest techniques for performing image segmentation. Multilevel thresholding is a simple and effective technique. The primary objective of bi-level or multilevel thresholding for image segmentation is to determine a best thresholding value. To achieve multilevel thresholding various techniques has been ...