Results 81 to 90 of about 17,318 (265)

Sketched Learning for Image Denoising

, 2021
The Expected Patch Log-Likelihood algorithm (EPLL) and its extensions have shown good performances for image denoising. It estimates a Gaussian mixture model (GMM) from a training database of image patches and it uses the GMM as a prior for denoising.
Hui Shi, Yann Traonmilin, Jean-François Aujol   +2 more
openaire   +2 more sources

Low‐Temperature Processed Optoelectronic Synapses With Enhanced Responsivity for Edge‐Oriented In‐Sensor Reservoir Computing

Advanced Materials Technologies, EarlyView.
Image pixels are converted into optical pulse sequences to stimulate the optoelectronic synaptic device, generating dynamic responses that form high‐dimensional features. These features improve classification efficiency and demonstrate strong potential for neuromorphic edge computing systems.
Jo‐Lin Chen, Shi‐Qian Guo, Yu‐Chuan Chiu, Po‐Tsun Liu   +3 more
wiley   +1 more source

A study of blind denoising algorithms for two-scale real images based on partial differential equations

Journal of Radiation Research and Applied Sciences
In order to better preserve the details and texture information in the image, a dual scale real image blind denoising algorithm based on partial differential equations is studied.
Yang Liu
doaj   +1 more source

The Noise Clinic: a Blind Image Denoising Algorithm [PDF]

, 2015
This paper describes the complete implementation of a blind image algorithm, that takes any digital image as input. In a first step the algorithm estimates a Signal and Frequency Dependent (SFD) noise model.
Jean-Michel Morel, Miguel Colom, Marc Lebrun   +2 more
core   +1 more source

TacScope: A Miniaturized Vision‐Based Tactile Sensor for Surgical Applications

Advanced Robotics Research, EarlyView.
TacScope is a compact, vision‐based tactile sensor designed for robot‐assisted surgery. By leveraging a curved elastomer surface with pressure‐sensitive particle redistribution, it captures high‐resolution 3D tactile feedback. TacScope enables accurate tumor detection and shape classification beneath soft tissue phantoms, offering a scalable, low‐cost ...
Md Rakibul Islam Prince, Sheeraz Athar, Pokuang Zhou, Yu She   +3 more
wiley   +1 more source

Image denoising method integrating ridgelet transform and improved wavelet threshold.

PLoS ONE
In the field of image processing, common noise types include Gaussian noise, salt and pepper noise, speckle noise, uniform noise and pulse noise. Different types of noise require different denoising algorithms and techniques to maintain image quality and
Bingbing Li, Yao Cong, Hongwei Mo
doaj   +1 more source

A clustering based denoising technique for range images of time of flight cameras

, 2008
A relatively new technique for measuring the 3D structure of visual scenes is provided by time of flight (TOF) cameras. Reflections of modulated light waves are recorded by a parallel pixel array structure.
Schoner, H., A. A. Dorrington, Dorrington, Adrian A., Payne, Andrew D., Moser, B., B. Heise, A. D. Payne, F. Bauer, B. Moser, H. Schoner, Heise, B., Bauer, F., M. J. Cree, Cree, Michael J.   +13 more
core   +1 more source

Low rank prior in single patches for non-pointwise impulse noise removal [PDF]

, 2015
This paper introduces a low rank prior in small oriented noise-free image patches: Considering an oriented patch as a matrix, a low-rank matrix approximation is enough to preserve the texture details in the optimally oriented patch.
Trucco, Emanuele; id_orcid, Pakleppa, Markus, Wang, Ruixuan   +2 more
core   +1 more source

Nonlocal Spatial–Spectral Neural Network for Hyperspectral Image Denoising

, 2022
Hyperspectral image (HSI) denoising is an essential preprocessing step to improve the quality of HSIs. The difficulty of HSI denoising lies in effectively modeling the intrinsic characteristics of HSIs, such as spatial-spectral correlation (SSC), global ...
Zhou, Jun, Qian, Yuntao, Xiong, Fengchao, Lu, Jianfeng, Fu, Guanyiman   +4 more
core   +1 more source

Continual Learning for Multimodal Data Fusion of a Soft Gripper

Advanced Robotics Research, EarlyView.
Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley   +1 more source