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Section: Publications & Resources
Publication: IEEE Signal Processing Letters
We consider the problem of recovering off-the-grid spikes from linear measurements in the context of Single Molecule Localization Microscopy (SMLM). State of the art model-based methods such as Over-Parametrized Continuous Orthogonal Matching Pursuit (OP-COMP) with Projected Gradient Descent (PGD) have been shown to successfully recover those signals.
Section: Events
Submission Deadline: 15 May 2025
Section: Publications & Resources
The IEEE Signal Processing Society (SPS) will hold a Special Election to fill the vacant President-Elect position, which will open on 6 February 2025 and close on 26 March 2025.
Section: Events
Date: 12-15 October 2025
Location: Lake Tahoe, CA, USA
Section: Events
Date: 1-4 November 2025
Location: Hong Kong
Section: Events
Date: 22 January 2025
Time: 10:00 AM ET (New York time)
Presenter(s): Yanning Shen
Section: Publications & Resources
The IEEE SPS congratulates the following SPS members who will receive the Society’s prestigious awards during ICASSP 2025 in India.
Section: Publications & Resources
Publication: IEEE Transactions on Computational Imaging
While snapshot hyperspectral cameras are cheaper and faster than imagers based on pushbroom or whiskbroom spatial scanning, the output imagery from a snapshot camera typically has different spectral bands mapped to different spatial locations in a mosaic pattern, requiring a demosaicing process to be applied to generate the desired hyperspectral image with full spatial and spectral resolution.
Section: Publications & Resources
Publication: IEEE Transactions on Computational Imaging
Magnetic Resonance Imaging (MRI) is a widely used imaging technique, however it has the limitation of long scanning time. Though previous model-based and learning-based MRI reconstruction methods have shown promising performance, most of them have not fully utilized the edge prior of MR images, and there is still much room for improvement.
Section: Publications & Resources
Publication: IEEE Transactions on Computational Imaging
We introduce ICE-TIDE, a method for cryogenic electron tomography (cryo-ET) that simultaneously aligns observations and reconstructs a high-resolution volume. The alignment of tilt series in cryo-ET is a major problem limiting the resolution of reconstructions. ICE-TIDE relies on an efficient coordinate-based implicit neural representation of the volume which enables it to directly parameterize deformations and align the projections.
