A pre-segmentation algorithm for computed tomography angiograms (CTA) is described. It is based on adaptive thresholding. The median axis of the binarized image provides arterial centerlines and estimates of the local radii. Boundary location is refined by analyzing radial intensity profiles in the vicinity of their intersections with the thresholds. The thresholding rule was learned on CTAs of...

We consider a wavelet thresholding approach to adaptive variance function estimation in heteroscedastic nonparametric regression. A data-driven estimator is constructed by applying wavelet thresholding to the squared first-order differences of the observations. We show that the variance function estimator is nearly optimally adaptive to the smoothness of both the mean and variance functions. Th...

A new adaptive speech enhancement system, which utilizes a second-generation wavelet transform (SGWT) decomposition and a novel adaptive subband thresholding technique, is presented. The adaptive thresholding technique is based on accurate estimation of subband segmental signal-to-noise ratio (SegSNR) and voiced/unvoiced classification of the speech. First, the speech signal is segmented and ea...

The objective of this paper is to develop a segmentation system in order to assist the surgeons to remove the portion of lung for the treatment of certain illness such as lung cancer, and tumours. The fissures of lung lobes are not seen by naked eyes in low dose CT image, there is a proposal for automatic segmentation system. The lung lobes and nodules in CT image are segmented using two stage ...

This paper is to develop a segmentation system in order to assist the surgeons for the treatment of certain illness such as lung cancer, and tumours.Lung cancer is one of the most frequently occurring cancer and it has a very low survival .Computer Aided Diagnosis (CAD) helps reducing the burden of radiation and improving the accuracy of abnormality detection during CT image interpretation. The...

The transformed l1 penalty (TL1) functions are a one parameter family of bilinear transformations composed with the absolute value function. When acting on vectors, the TL1 penalty interpolates l0 and l1 similar to lp norm (p ∈ (0, 1)). In our companion paper, we showed that TL1 is a robust sparsity promoting penalty in compressed sensing (CS) problems for a broad range of incoherent and cohere...

In the context of wavelet denoising and compression, we study minimum description length (MDL) criteria for model selection criteria as exible forms of thresholding. Mixture MDL methods based on a single Laplacian, a two-piece Laplacian, and a generalized Gaussian prior are shown to be adaptive thresholding rules. While achieving mean squared error performance comparable with other popular thre...

In the context of wavelet denoising and compression, we study minimum description length (MDL) criteria for model selection criteria as exible forms of thresholding. Mixture MDL methods based on a single Laplacian, a two-piece Laplacian, and a generalized Gaussian prior are shown to be adaptive thresholding rules. While achieving mean squared error performance comparable with other popular thre...

There are many existing studies released in the field of Computer Vision, especially Automatic License Plate Recognition. However, most them focused on using one method at time, such as Thresholding algorithms, Edge Detections or Morphological transformations. This research paper proposes to automate plate recognition process, by combining four algorithms from three methods mentioned above: Ada...