6 days ago · Our Uformer-ICS is an end-to-end framework that simultaneously learns the sampling and reconstruction processes. Experimental results demonstrate its superior ...

Jun 10, 2024 · Existing works propose to sample the image under a two-stage or multiple-stage framework, which realizes the adaptive sampling based on the texture or saliency ...

Jun 21, 2024 · Purpose: To propose a self-supervised deep learning-based compressed sensing MRI (DL-based CS-MRI) method named "Adaptive Self-Supervised Consistency Guided ...

Jun 27, 2024 · Current compression algorithms for NX 3D image models can be classified into two categories: a combination of traditional compressive sensing and reconstruction ...

Jun 13, 2024 · In this paper, we propose and study the use of alternating direction algorithms for several $\ell_1$-norm minimization problems arising from sparse solution ...

Jun 16, 2024 · Deep unfolding networks (DUNs), renowned for their in- terpretability and superior performance, have invigorated the realm of compressive sensing (CS).

Jun 11, 2024 · A Bayesian compressive sensing framework is developed for video reconstruction based on the color coded aperture compressive temporal imaging (CACTI) system.

Jun 26, 2024 · Purpose: We present a method that combines compressed sensing with parallel imaging that takes advantage of the structure of the sparsifying transformation.

Jun 21, 2024 · We consider the reconstruction problem of video snapshot compressive imaging (SCI), which captures high-speed videos using a low-speed 2D sensor (detector).

Jun 25, 2024 · In this work, our proposed DCCM and DCCM-Net enable high-speed confocal imaging at ultra-low sampling ratios for deeply compressed image reconstruction.