Filtering noise is a fundamental part of data preparation that enhances image quality for applications such as object segmentation, detection, and recognition. Various noise reduction techniques are proposed in the literature, including the use of median, Gaussian, and bilateral filters.
arXiv:2607. 02952v1 Announce Type: cross Abstract: Convolutional Neural Networks (CNNs) achieve strong denoising performance by exploiting spatial context from neighboring pixels.
arXiv:2507.08375v2 Announce Type: replace Abstract: Video restoration and enhancement are critical not only for improving visual quality, but also as essential pre-processing steps to boost the perfo...
arXiv:2608.29038v1 Announce Type: new Abstract: Noise poses a widespread challenge in signal processing, particularly when it comes to denoising images. Although convolutional neural networks (CNNs)...
arXiv:2504.10201v3 Announce Type: replace Abstract: In this paper, we introduce a synthetic image generator relying on a few simple principles, specifically focusing on geometric modeling, textures,...
The paper introduces DeepBM3D, a fully differentiable neural network that emulates the collaborative filtering strategy of BM3D for image denoising. It integrates non‑local patch grouping, DCT‑domain filtering with learned Wiener weights, and multi‑stage refinement, guided by lightweight convolutional feature extractors. Experiments demonstrate that DeepBM3D outperforms classical and hybrid baselines, competes with FFDNet at low to moderate noise levels, and excels on images with repetitive textures.
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arXiv:2503. 22223v2 Announce Type: replace Abstract: The semi-airborne transient electromagnetic method (SATEM) is capable of conducting rapid surveys over large-scale and hard-to-reach areas.
arXiv:2606. 08033v1 Announce Type: cross Abstract: Cracks are a critical indicator of building health, and early stage identification is fundamental to prevent harmful damages.
arXiv:2609.37870v1 Announce Type: new Abstract: Raindrops adhered to camera lens or windshield are inevitable in rainy scenes and can become an issue for many computer vision systems such as autonomo...
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