Results 71 to 80 of about 9,413,043 (217)
Dual-Channel Contrast Prior for Blind Image Deblurring
In this article, a dual-channel contrast prior (Dual-CP) is proposed for blind image deblurring. The prior is motivated by the observation that image contrast will significantly degenerate after the blurring process, which is proved in both ...
Dayi Yang, Xiaojun Wu
doaj +1 more source
From Nano Robotic Manipulation to Nano Manipulation Robot
This review addresses a critical research gap by summarizing advancements in nano robotic manipulation, tracing its evolution from passive observation to autonomous nanomanipulation robots. It explores the interplay of observation, construction, and operation, unveiling fundamental principles of atomic‐scale control. The review establishes a systematic
Zhan Yang +6 more
wiley +1 more source
In this chapter, Bussgang blind deconvolution techniques are reviewed in the general Bayesian framework of minimum mean square error (MMSE) estimation, and some recent activities of the authors on both single-channel and multichannel blind image ...
Scarano G. +4 more
core +2 more sources
Temperature‐Resilient Polymeric Memristors for Effective Deblurring in Static and Dynamic Imaging
A thermally stable organic memristor based on a thiadiazolobenzotriazole (TBZ) and 2,5‐Dioctyl‐3,6‐di(thiophen‐2‐yl)pyrrolo[3,4‐c]pyrrole‐1,4(2H,5H)‐dione (DPP)‐based conjugated polymer is presented, demonstrating reliable, gradual resistance switching across a wide temperature range (153–573 K).
Ziyu Lv +15 more
wiley +1 more source
Fast Weighted Total Variation Regularization Algorithm for Blur Identification and Image Restoration
Images obtained from unconstrained environments may be blurred by unknown kernels and affected due to noise. This paper presents a new total variation minimization-based method for blindly deblurring such images. Unlike the alternating optimization-based
Haiying Liu +3 more
doaj +1 more source
This review explores deconvolution techniques in optical coherence tomography (OCT), addressing resolution degradation from point‐spread functions (PSF). It reviews foundational principles (e.g., Richardson‐Lucy deconvolution) to advanced AI‐driven methods, emphasizing clinical translation and interdisciplinary collaboration. Real‐world implementations
Syeda Aimen Abbasi +6 more
wiley +1 more source
Improved conditional diffusion model for image super‐resolution
Our article introduces a diffusion model based on Mean‐Reverting Stochastic Differential Equations (SDE), leveraging ENAFBlocks to enhance noise prediction performance compared to traditional ResBlocks. The Mean‐Reverting SDE utilizes low‐resolution images as means to mitigate diffusion model randomness, while an LR Encoder captures hidden information ...
Rui Wang, Ningning Zhou
wiley +1 more source
Plenoptic Image Motion Deblurring
We propose a method to remove motion blur in a single light field captured with a moving plenoptic camera. Since motion is unknown, we resort to a blind deconvolution formulation, where one aims to identify both the blur point spread function and the ...
Paramanand Chandramouli +7 more
core +1 more source
Arbitrarily shaped Point Spread Function (PSF) estimation for single image blind deblurring [PDF]
The research paper focuses on a challenging task faced in blind image deblurring (BID). It relates to the estimation of arbitrarily shaped (nonparametric or complex shaped) point spread functions (PSFs) of motion blur caused by camera handshake.
Khan, Aftab, Yin, Hujun; id_orcid
core +1 more source
Deformable Attention Network for Efficient Space‐Time Video Super‐Resolution
Recent space‐time video super‐resolution (STVSR) works combine temporal interpolation and spatial super‐resolution in a unified framework, they face challenges in computational complexity across both temporal and spatial dimensions, particularly in achieving accurate intermediate frame interpolation and efficient temporal information utilisation.
Hua Wang +3 more
wiley +1 more source

