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Watermark detection is a way of verifying the existence of a watermark in a watermarking scheme used for copyright protection of digital data. Statistical modeling of wavelet subband coefficients has been extensively used in watermark detection. The effectiveness of a watermarking scheme depends directly on how the wavelet coefficients are modeled. It is known that the vector-based hidden Markov model...
Despecking is an essential part of any synthetic aperture radar (SAR) imagery systems. In this work, we propose a new despeckling method for SAR images in the wavelet domain. The performance of a method can be significantly improved by taking into account the statistical dependencies between the wavelet coefficients. It has been shown that the vector-based hidden Markov model (HMM) is capable of capturing...
Salient regions are the most dominant parts of an image, which capture human visual system's attention. Finding computational methods that are able to detect salient regions especially in images with messy background is a challenging task. In this paper, a novel segment-based saliency detection method using the wavelet transform is proposed. The human beings are attracted by objects or regions rather...
There are a number of image denoising methods in the wavelet domain using statistical models. It is known that the performance of such methods can be significantly improved by taking into account the statistical dependencies between the wavelet coefficients. It is shown that the vector-based hidden Markov model (VB-HMM) is capable of capturing both the subband marginal distribution and the inter-scale,...
The wavelet coefficients of images show heavy-tailed marginal statistics as well as strong inter- and intra-subbands and across orientations dependencies. The vector-based hidden Markov model (HMM) has been shown to be an effective statistical model for wavelet coefficients, which is capable of capturing both the subband marginal distribution and the inter-scale and intra-scale dependencies of the...
Medical ultrasound images are widely used for diagnostic purposes. A major problem regarding these images is in their inherent corruption by speckle noise in a multiplicative fashion. The presence of speckle noise severely hampers the interpretation and analysis of medical ultrasound images. This paper presents a fast and reliable wavelet-based method for reducing the speckle in medical ultrasound...
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