Results 11 to 20 of about 225,507 (258)

A Denoising Method Using Deep Image Prior to Human-Target Detection Using MIMO FMCW Radar [PDF]

Sensors, 2022
A Multiple-Input Multiple-Output (MIMO) Frequency-Modulated Continuous Wave (FMCW) radar can provide a range-angle map that expresses the signal power against each range and angle. It is possible to estimate object locations by detecting the signal power
Koji Endo, Kohei Yamamoto, Tomoaki Ohtsuki   +2 more
doaj   +2 more sources

Deep image prior for undersampling high-speed photoacoustic microscopy [PDF]

Photoacoustics, 2021
Photoacoustic microscopy (PAM) is an emerging imaging method combining light and sound. However, limited by the laser’s repetition rate, state-of-the-art high-speed PAM technology often sacrifices spatial sampling density (i.e., undersampling) for ...
Tri Vu, Anthony DiSpirito, III, Daiwei Li, Zixuan Wang, Xiaoyi Zhu, Maomao Chen, Laiming Jiang, Dong Zhang, Jianwen Luo, Yu Shrike Zhang, Qifa Zhou, Roarke Horstmeyer, Junjie Yao   +12 more
doaj   +2 more sources

Low-Light Image Enhancement via Retinex-Style Decomposition of Denoised Deep Image Prior [PDF]

Sensors, 2022
Low-light images are a common phenomenon when taking photos in low-light environments with inappropriate camera equipment, leading to shortcomings such as low contrast, color distortion, uneven brightness, and high loss of detail.
Xianjie Gao, Mingliang Zhang, Jinming Luo   +2 more
doaj   +2 more sources

Deep Image Prior Amplitude SAR Image Anonymization

Remote Sensing, 2023
This paper presents an extensive evaluation of the Deep Image Prior (DIP) technique for image inpainting on Synthetic Aperture Radar (SAR) images. SAR images are gaining popularity in various applications, but there may be a need to conceal certain ...
Edoardo Daniele Cannas, Sara Mandelli, Paolo Bestagini, Stefano Tubaro, Edward J. Delp   +4 more
doaj   +2 more sources

DIPLI: deep image prior lucky imaging for blind astronomical image restoration [PDF]

Scientific Reports
Modern image restoration and super-resolution methods utilize deep learning due to its superior performance compared to traditional algorithms. However, deep learning typically requires large labeled training datasets, which are rarely available in ...
Suraj Singh, Anastasiia Batsheva, Oleg Y. Rogov, Ahmed Bouridane   +3 more
doaj   +2 more sources

Noise-Resistant Demosaicing with Deep Image Prior Network and Random RGBW Color Filter Array [PDF]

Sensors, 2022
In this paper, we propose a deep-image-prior-based demosaicing method for a random RGBW color filter array (CFA). The color reconstruction from the random RGBW CFA is performed by the deep image prior network, which uses only the RGBW CFA image as the ...
Edwin Kurniawan, Yunjin Park, Sukho Lee
doaj   +2 more sources

DIPPAS: a deep image prior PRNU anonymization scheme [PDF]

EURASIP Journal on Information Security, 2022
Source device identification is an important topic in image forensics since it allows to trace back the origin of an image. Its forensics counterpart is source device anonymization, that is, to mask any trace on the image that can be useful for ...
Francesco Picetti, Sara Mandelli, Paolo Bestagini, Vincenzo Lipari, Stefano Tubaro   +4 more
doaj   +4 more sources

Joint Demosaicing and Denoising Based on a Variational Deep Image Prior Neural Network [PDF]

Sensors, 2020
A joint demosaicing and denoising task refers to the task of simultaneously reconstructing and denoising a color image from a patterned image obtained by a monochrome image sensor with a color filter array.
Yunjin Park, Sukho Lee, Byeongseon Jeong, Jungho Yoon   +3 more
doaj   +2 more sources

Diffraction tomography with a deep image prior. [PDF]

Opt Express, 2020
We present a tomographic imaging technique, termed Deep Prior Diffraction Tomography (DP-DT), to reconstruct the 3D refractive index (RI) of thick biological samples at high resolution from a sequence of low-resolution images collected under angularly varying illumination.
Zhou KC, Horstmeyer R.
europepmc   +4 more sources

Rethinking Deep Image Prior for Denoising [PDF]

2021 IEEE/CVF International Conference on Computer Vision (ICCV), 2021
Deep image prior (DIP) serves as a good inductive bias for diverse inverse problems. Among them, denoising is known to be particularly challenging for the DIP due to noise fitting with the requirement of an early stopping. To address the issue, we first analyze the DIP by the notion of effective degrees of freedom (DF) to monitor the optimization ...
Yeonsik Jo, Se Young Chun, Jonghyun Choi
openaire   +2 more sources