Restoration Medical Images from Speckle Noise Using Multifilters

Kadhim, Maha Abdulameer

doi:10.1109/icaccs51430.2021.9441814

Cited by 11 publications

(4 citation statements)

References 12 publications

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“…Under such scenarios, a spatial averaging [10,306] to smoothen the image would be useful. In other cases, when there is too much speckle noise and hinders the detection of small damage, a median filter or other moving-window filters (convolution) would help [307,308]. Removal of the speckle noise based on local statistics filtering with a least-square estimation of first-order Taylor series expansion of an image had been proposed too [309].…”

Section: Improvement Of Image Quality Based On Image Processingmentioning

confidence: 99%

Guided ultrasonic waves propagation imaging: a review

Chia¹,

Lee²,

Harmin³

et al. 2023

Meas. Sci. Technol.

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This article presents a comprehensive review of the laser-based guided ultrasonic waves propagation imaging (G-UPI) system and respective signal/data processing methods related to the nondestructive testing and evaluation of thin-walled structures. The primary goal of this study is to review and recognize various processing methods, explain the working principles of the most influential methods, and highlight outstanding capabilities. In addition, the suitability of the methods for multiple types of damage and defect in various materials and structures are presented. At the same time, success stories of difficult-to-inspect cases are highlighted. Its secondary goal is to compare and discuss the merits and demerits of the laser-scanning part of the system for ultrasound generation and acquisition to provide a guideline for scanning scheme or hardware selection. Finally, the potential challenges and prospects of the G-UPI are discussed. It is expected that this review would serve as an entrance key for newcomers and a reference point for researchers to explore the opportunities for further improvement in the laser ultrasound-based evaluation of critical engineering structures.

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Section: Improvement Of Image Quality Based On Image Processingmentioning

confidence: 99%

Guided ultrasonic waves propagation imaging: a review

Chia¹,

Lee²,

Harmin³

et al. 2023

Meas. Sci. Technol.

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“…Presently, advanced medical assessment is inconceivable without the use of medical imaging techniques [1]. Due to the 20th century's remarkable advancements in atomic physics, doctors are now able to see inside a patient's body to identify anatomical structures and rule out congenital abnormalities [2], [3]. In the realm of computational imaging, digital images frequently experience the unwelcome presence of noise, which lowers the visual quality and makes it more difficult to accurately analyze and interpret the underlying data.…”

Section: ) Introductionmentioning

confidence: 99%

Enhancing the Quality of 2D and 3D Image Using Block Matching 3D and Fuzzy Hybrid Model Based on Random Noise Reduction

Biswas,

Bushra,

Islam

et al. 2024

Preprint

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Medical imaging has become an important research field that embraces a great variety of sciences. Imaging is the central science of measurement in the diagnosis and treating diseases. The effort of technological progress has made possible human imaging starting from a single molecule to the whole body. A new strategy for suppressing random noise in medical images has been proposed in this research. This methodology is founded on a fuzzy filter which follows BM3D (Block Matching 3D) and fuzzy hybrid model. In this comprehensive study, we address the challenges posed by random noise in 2D and 3D images through a unique approach of image denoising. As high-quality medical imaging (Ultrasound, CT-Scan and MRI) is required to obtain a quick and accurate diagnosis. But the problem is that the image can frequently be contaminated by several types of noises including speckle noise, salt & pepper noise, and Gaussian noise. For RGB and grayscale images, some traditional fuzzy membership function is adeptly employed to eliminate these random noises. But here, our proposed research methodology also encompasses 2D and 3D techniques for medical and non-medical image denoising. This research contributes to advancing the field, offering insights into effective strategies for enhancing the quality and accuracy of images crucial for diagnostic and treatment purposes.

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“…To remove blurring and noise from degraded images, restoration processes must be performed. The goal of the restoration process is to estimate an image that is as close as possible to the original image f (x, y), based on its degraded counterpart g(x, y) [5]. There are two types of image deconvolution algorithms: blind (in which both PSF and noise are unknown) and non-blind (in which both PSF and noise are known).…”

Section: Introductionmentioning

confidence: 99%

An Adaptive Richardson-Lucy Algorithm for Medical Image Restoration

Yaqoub¹,

Al-Ani²

2023

JTIT

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Image restoration is the process of estimating the original image content from a degraded picture. In this paper, the Richardson-Lucy iterative algorithm was developed to improve the quality of degraded medical images. It has been assumed that medical images are exposed to two types of degradation. The first type is the blur function in the Gaussian form with different widths, i.e. σ = 1 , 2, and 3. The second type of degradation was assumed to be of the independent white Gaussian noise type with different signal-to-noise ratio values: SNR = 10, 50 , and 100. The results obtained from the adaptive filter are compared, quantitatively, with different conventional filters: inverse, Wiener, and constraint least square, by applying different measures, such as: power signal to noise ratio (PSNR), structural similarity index (SSID), and root mean square error (RMSE). The comparison showed that the adaptive recovery filter achieves better results.

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Restoration Medical Images from Speckle Noise Using Multifilters

Cited by 11 publications

References 12 publications

Guided ultrasonic waves propagation imaging: a review

Guided ultrasonic waves propagation imaging: a review

Enhancing the Quality of 2D and 3D Image Using Block Matching 3D and Fuzzy Hybrid Model Based on Random Noise Reduction

An Adaptive Richardson-Lucy Algorithm for Medical Image Restoration

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