A new speckle filtering method for ultrasound images based on a weighted multiplicative total variation

Hacini, Meriem; Hachouf, Fella; Djemal, Khalifa

doi:10.1016/j.sigpro.2013.12.008

Cited by 33 publications

(9 citation statements)

References 42 publications

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“…Such noise is generally more difficult to remove than additive noise [ 23 ]. This type of distortion appears in sonar, laser, and synthetic aperture radar (SAR), and it depends on the structure of the material being imaged and various acquisition parameters [ 24 ]. Speckle noise is a random process and can be modeled using gamma, Rayleigh, and Fisher-Tippett distribution [ 25 – 27 ].…”

Section: Methodsmentioning

confidence: 99%

“…Speckle noise is a random process and can be modeled using gamma, Rayleigh, and Fisher-Tippett distribution [ 25 – 27 ]. In our work, the simplified speckle noise model has been employed, since it has been applied successfully in many studies [ 11 , 24 , 28 , 29 ].

where u ( x ), v ( x ), and n ( x ) denote the observed signal, original unknown signal, and zero-mean Gaussian noise, respectively.…”

Section: Methodsmentioning

confidence: 99%

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Digital Path Approach Despeckle Filter for Ultrasound Imaging and Video

Szczepański

Radlak

2017

Journal of Healthcare Engineering

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We propose a novel filtering technique capable of reducing the multiplicative noise in ultrasound images that is an extension of the denoising algorithms based on the concept of digital paths. In this approach, the filter weights are calculated taking into account the similarity between pixel intensities that belongs to the local neighborhood of the processed pixel, which is called a path. The output of the filter is estimated as the weighted average of pixels connected by the paths. The way of creating paths is pivotal and determines the effectiveness and computational complexity of the proposed filtering design. Such procedure can be effective for different types of noise but fail in the presence of multiplicative noise. To increase the filtering efficiency for this type of disturbances, we introduce some improvements of the basic concept and new classes of similarity functions and finally extend our techniques to a spatiotemporal domain. The experimental results prove that the proposed algorithm provides the comparable results with the state-of-the-art techniques for multiplicative noise removal in ultrasound images and it can be applied for real-time image enhancement of video streams.

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Section: Methodsmentioning

confidence: 99%

where u ( x ), v ( x ), and n ( x ) denote the observed signal, original unknown signal, and zero-mean Gaussian noise, respectively.…”

Section: Methodsmentioning

confidence: 99%

Digital Path Approach Despeckle Filter for Ultrasound Imaging and Video

Szczepański

Radlak

2017

Journal of Healthcare Engineering

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“…This new methodology contributes to a reliable noise characterisation at specific positions in the analysis area. Modern speckle reduction techniques based on homomorphic filtering [16], diffusion models [17], or total variation estimation [18], could take advantage of this informed new feature.…”

Section: Introductionmentioning

confidence: 99%

Rician Beamforming: Despeckle Method via Coarray Projection Stochastic Analysis

Yagüe-Jiménez¹,

Rodríguez²,

Parrilla³

et al. 2020

Applied Sciences

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Current computation capabilities normal, Delay and Sum (DAS) and Total Focusing Method (TFM) allow new definitions for beamformers. In this paper, a new beamforming method is proposed. It exploits diversity across pixel data after focusing process. The method is based on statistical analysis and sparse array concept. It avoids common aberrations introduced by beamforming process without loosing the original image texture, producing a better quality image. We evaluate the proposed method through simulation on standard phantoms. Images resulting from our novel method display better quality and provide localised estimations on image noise.

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“…This kind of noise is common to laser, sonar and synthetic aperture radar (SAR) imagery and depends on the structure of imaged tissue and various imaging parameters [5]. According to the literature, speckle noise can be approximated by the Gamma distribution [6], the Rayleigh distribution [7] or the Fisher-Tippett distribution [8].…”

Section: Introductionmentioning

confidence: 99%

“…(1) with γ = 0.5 fits better to data than the simple multiplicative model with γ = 1 or the Rayleigh model. This model has been employed in our work, since it has been used successfully in many studies [5,10,11].…”

Section: Introductionmentioning

confidence: 99%

Escaping path approach for speckle noise reduction

Szczepański

Radlak

2015

SPIE Proceedings

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A novel fast filtering technique for multiplicative noise removal in ultrasound images was presented in this paper. The proposed algorithm utilizes concept of digital paths created on the image grid presented in [1]adapted to the needs of multiplicative noise reduction. The new approach uses special type of digital paths so called Escaping Path Model and modified path length calculation based on topological as well as gray-scale distances. The experiments confirmed that the proposed algorithm achieves a comparable results with the existing state-of-theart denoising schemes in suppressing multiplicative noise in ultrasound images.

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A new speckle filtering method for ultrasound images based on a weighted multiplicative total variation

Cited by 33 publications

References 42 publications

Digital Path Approach Despeckle Filter for Ultrasound Imaging and Video

Digital Path Approach Despeckle Filter for Ultrasound Imaging and Video

Rician Beamforming: Despeckle Method via Coarray Projection Stochastic Analysis

Escaping path approach for speckle noise reduction

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