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, 2011 Matter of discussion in this Ph. D. thesis is SAR (Synthetic Aperture Radar) image denoising. Main elements of innovation are the introduction of SAR-BM3D, a denoising algorithm optimized for SAR data, and the introduction of a benchmark which enables ...
Poderico, Mariana
core +1 more source
Heterogeneous Window Transformer for Image Denoising [PDF]
IEEE Transactions on Systems, Man & Cybernetics. SystemsDeep networks can usually depend on extracting more structural information to improve denoising results. However, they may ignore correlation between pixels from an image to pursue better-denoising performance.
Chunwei Tian +4 more
semanticscholar +1 more source
CVF-SID: Cyclic multi-Variate Function for Self-Supervised Image Denoising by Disentangling Noise from Image [PDF]
Computer Vision and Pattern Recognition, 2022 Recently, significant progress has been made on image denoising with strong supervision from large-scale datasets. However, obtaining well-aligned noisy-clean training image pairs for each specific scenario is complicated and costly in practice ...
Reyhaneh Neshatavar +3 more
semanticscholar +1 more source
Joint Image Denoising with Gradient Direction and Edge-Preserving Regularization
, 2021 Joint image denoising algorithms use the structures of the guidance image as a prior to restore the noisy target image. While the provided guidance images are helpful to improve the denoising performance, the denoised edges are most likely to be blurred ...
Li, Pengliang +4 more
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Denoising of Image Gradients and Total Generalized Variation Denoising [PDF]
Journal of Mathematical Imaging and Vision, 2018 We revisit total variation denoising and study an augmented model where we assume that an estimate of the image gradient is available. We show that this increases the image reconstruction quality and derive that the resulting model resembles the total generalized variation denoising method, thus providing a new motivation for this model.
Birgit Komander +2 more
openaire +4 more sources
RESIDUAL LEARNING BASED IMAGE DENOISING AND COMPRESSION USING DNCNN
ICTACT Journal on Image and Video Processing, 2022 Image compression has become an essential subfield in image processing for many generations. This should be an effective process with decreasing this amount about a file format through frames unless significantly lowering from an exceptional standard ...
Savaram Shaliniswetha +1 more
doaj +1 more source
Deep Orthogonal Transform Feature for Image Denoising
IEEE Access, 2020 Recently, CNN-based image denoising has been investigated and shows better performance than conventional vision based techniques. However, there are still a couple of limits that are weak partly in restoring image details like textured regions or produce
Yoon-Ho Shin +3 more
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EURASIP Journal on Wireless Communications and Networking, 2021 As an important part of smart city construction, traffic image denoising has been studied widely. Image denoising technique can enhance the performance of segmentation and recognition model and improve the accuracy of segmentation and recognition results.
Chunzhi Wang +4 more
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True 4D Image Denoising on the GPU
International Journal of Biomedical Imaging, 2011 The use of image denoising techniques is an important part of many medical imaging applications. One common application is to improve the image quality of low-dose (noisy) computed tomography (CT) data.
Anders Eklund +2 more
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Image Denoising Algorithm Based on Gradient Domain Guided Filtering and NSST
IEEE Access, 2023 Traditional image denoising methods, which do not depend on data training, have good interpretability. However, traditional image denoising methods hardly achieve the denoising effect of deep learning methods.
Zhe Li +3 more
doaj +1 more source