Two stage image de-noising by SVD on large scale heterogeneous anisotropic diffused image data

Khan, Nafis Uddin; Arya, K. V.

doi:10.1007/s11042-018-6144-9

Cited by 3 publications

(1 citation statement)

References 24 publications

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“…Very recently, a fuzzy based approximated anisotropic diffusion [38] has been presented, which is quite effective for impulse noise removal from standard scientific and medical images. A detailed overview of various anisotropic diffusion techniques [48][49] [50][51] [52][53] used for image enhancement and de-noising is provided in [39]. In all the above anisotropic diffusion filters, the smoothing results in ultrasound images are effective but fail to restore fine details.…”

Section: Anisotropic Diffusionmentioning

confidence: 99%

A Two Phase Ultrasound Image De-speckling Framework by Nonlocal Means on Anisotropic Diffused Image Data

Thakur

Khan

Sharma

2023

IJCAI

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Image de-speckling is one of the most challenging issues in multimedia imaging systems. All of the available speckle noise reduction filters are nearly noise reduction capable, but they fail to restore subtle features such as low grey level edges and fine details against a low contrast background. Nonlocal mean filtering and anisotropic diffusion are two popular and effective methods for image despeckling while preserving detail. This paper presents a two-phase ultrasound image de-speckling framework by utilizing the capability of the non-local mean filtering method for de-speckling and edge preservation on anisotropic diffused images. The prior image smoothing along with edge preservation and contrast enhancement by anisotropic diffusion is carried out in the first phase, which is then followed by the non-local means method for de-speckling and edge sharpening in the next phase. The degree of speckle noise attenuation is measured on low-contrast standard and ultrasound images and compared to state-of-the-art and advanced anisotropic diffusion techniques and non-local means methods. The percentage improvement of PSNR over the existing methods is found to be in the range of 2.06% to 46.68%. The experimental results show that the proposed method is capable of reducing noise and preserving edges better than existing speckle reduction filters.Povzetek: Predstavljen je dvofazni pristop za odstranjevanje šuma iz ultrazvočnih slik, ki se je v primerjavi z obstoječimi filtri za zmanjšanje šuma izkazal za boljšega v ohranjanju robov in zmanjševanju šuma.

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