Results 281 to 290 of about 116,500 (328)

LDCT image denoising algorithm based on two-dimensional variational mode decomposition and dictionary learning. [PDF]

Sci Rep
Han Y, Liu X, Zhang N, Wang Y, Ju M, Ding Y.   +5 more
europepmc   +1 more source

Effectiveness of Fourier, Wiener, Bilateral, and CLAHE Denoising Methods for CT Scan Image Noise Reduction

Mst Jannatul Kobra, Arman Mohammad Nakib, Peter Mweetwa, Md Owahedur Rahman   +3 more
openalex   +2 more sources

Investigating the use of signal detection information in supervised learning-based image denoising with consideration of task-shift. [PDF]

J Med Imaging (Bellingham)
Li K, Li H, Anastasio MA.
europepmc   +1 more source

VLSI implementation of a modified min-max median filter using an area and power competent tritonic sorter for image denoising. [PDF]

Sci Rep
Christudhas C, Fathima A.
europepmc   +1 more source

Deep learning-based PET image denoising and reconstruction: a review. [PDF]

Radiol Phys Technol
Hashimoto F, Onishi Y, Ote K, Tashima H, Reader AJ, Yamaya T.   +5 more
europepmc   +1 more source

Adaptive denoising method for EBAPS images captured under ultra-low-light conditions via scintillation noise detection and region-specific filtering

Yilun Wang, Zhong-Jun Ding, Jian Liu, Honggang Wang, Yunsheng Qian   +4 more
openalex   +1 more source

All-optical image denoising using a diffractive visual processor. [PDF]

Light Sci Appl
Işıl Ç, Gan T, Ardic FO, Mentesoglu K, Digani J, Karaca H, Chen H, Li J, Mengu D, Jarrahi M, Akşit K, Ozcan A.   +11 more
europepmc   +1 more source

Research on improved black widow algorithm for medical image denoising. [PDF]

Sci Rep
Qu H, Liu K, Zhang L.
europepmc   +1 more source

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Progressive Image Denoising

IEEE Transactions on Image Processing, 2014
Image denoising continues to be an active research topic. Although state-of-the-art denoising methods are numerically impressive and approch theoretical limits, they suffer from visible artifacts.While they produce acceptable results for natural images, human eyes are less forgiving when viewing synthetic images.
Claude, Knaus, Matthias, Zwicker
openaire   +2 more sources

Fractal image denoising

IEEE Transactions on Image Processing, 2003
Over the past decade, there has been significant interest in fractal coding for the purpose of image compression. However, applications of fractal-based coding to other aspects of image processing have received little attention. We propose a fractal-based method to enhance and restore a noisy image.
Mohsen, Ghazel, George H, Freeman, Edward R, Vrscay   +2 more
openaire   +2 more sources