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Blind deblurring attempts to recover the latent sharp image from a blurred one. Such task is a well-known ill-posed inverse problem and is therefore usually solved as a posteriori probability estimation, incorporating prior information on natural images. In this paper, we propose a general blind noisy deblurring model based on hyper Laplacian (HL) in gradient domain and kernel spectra prior. This...
A non-cooperative source localization method utilizing the time difference of arrival (TDOA) of a rotating short baseline on a single observer is proposed in this paper. The localization bias caused by constant TDOA measurement bias is analyzed. It can be proved that this localization bias can be auto-eliminated when the sum of baseline orientation vectors that correspond with all TDOA measurements...
In this paper we present a research on identification of audio recording devices from background noise, thus providing a method for forensics. The audio signal is the sum of speech signal and noise signal. Usually, people pay more attention to speech signal, because it carries the information to deliver. So a great amount of researches have been dedicated to getting higher Signal-Noise-Ratio (SNR)...
Removing the noise while keeping the image features like edges, textures is a challenging problem in image denoising. Because it is an under-determined problem, defining appropriate image priors to regularize the problem plays an important role. Recently a popular one among proposed image priors is the graph Laplacian regularizer, which can exploit the local geometry structure of the image. Introducing...
Analysis dictionary learning (ADL) aims to design dictionaries from training data based on an analysis sparse representation model. Sparse analysis model is an alternative model to the sparse synthesis model used in a variety of signal processing areas. This paper introduces a new ADL method called MAX-ADL algorithm used to estimate the dictionary directly from the noisy measurements. The algorithm...
In conventional speech enhancement algorithms, the most used technique for noise suppression is the attenuating filter, mainly because that the sign or phase of the clean speech and noise coefficients are assumed to be coincident. However, the amplitude of the noisy speech coefficient may not always be bigger than that of the clean speech in fact. Considering the two stats of noise signals in DCT...
In side channel attacks (SCA), noise has been a hot topic for affecting the quality of obtained observations. In this paper, we propose a kind of improved wavelet transform denoising method based on singular spectral analysis (SSA) and detrended fluctuation analysis (DFA). Principal signal component in SSA can be selected by DFA adaptively, and residual part can be denoised by wavelet transform to...
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