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IEEE Signal Processing Society Blog


The SPS blog aims to raise awareness about signal processing and Society-related topics to a general interest audience in an engaging, informal, and non-technical way. If you're interested in contributing to the SPS blog, please contact the SPS Blog Team at sps-blog@ieee.org for more information.

Underwater Image Enhancement via a Robust yet Efficient Dual Prior Optimized Method

By: 
Weidong Zhang, Songlin Jin, Peixian Zhuang, Zheng Liang, Chongyi Li

Underwater images are highly susceptible to quality degradation due to light's scattering and absorption [1,2]. Unfortunately, underwater images with deteriorating quality impose many limitations in following visual perception analysis and practical underwater applications.

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Can Lensless Cameras Redefine Depth of Field in Photography?

By: 
Dr. Jose Reinaldo Cunha Santos A V Silva Neto

This post introduces a novel approach to extending the depth of field (DOF) in lensless cameras using optimized radial coded masks. Our proposed method overcomes the limitations of previous and generic coded mask designs by employing a radial-shape-constrained optimization procedure, resulting in improved optical transfer functions while enabling extended DOF. Through simulations and prototype experiments, we demonstrate that our optimized radial mask achieves superior imaging quality compared to hand-crafted radial patterns and larger DOF than non-radial masks.

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IEEE SustainTech Leadership Forum Draws World’s Top Technical and Sustainability Experts

By: 
IEEE Signal Processing Society

The new global thought leadership event brought together industry movers and shakers to discuss the future of Buildings and Factories in the Built Environment.

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Occlusion-Aware Human Mesh Model-Based Gait Recognition

By: 
Prof. Chi Xu

An occlusion-aware model for gait video processing uses SMPL-based human mesh models and machine learning to achieve superior recognition in challenging surveillance videos.

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FSIM: A Feature Similarity Index for Image Quality Assessment

By: 
Dr. Lin Zhang

We propose a novel low-level feature similarity (FSIM) induced FR IQA metric, namely, FSIM. FSIM can measure image quality automatically and consistently with human perception.

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Physics Makes Black-box Deep Learning Models Transparent

By: 
Prof. Zicheng Liu

Electromagnetic inverse scattering problems (ISPs) are crucial in noninvasive imaging but challenging due to nonlinearity and computational costs. This blog explores machine learning-based ISP solvers with physics-guided loss functions, emphasizing the role of near-field priors and multiple-scattering effects. Numerical experiments highlight the advantages and limitations of these approaches.

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Optimize Your Signal Processing with Bayesian Optimization

By: 
Richard Cornelius Suwandi

Explore how Bayesian optimization enhances signal processing applications by providing efficient algorithm design solutions in the signal processing toolbox.

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Devising Transformers as an Autoencoder for Unsupervised Multivariate Time Series Imputation

By: 
Dr. Aykut Koç

Inspired by the capabilities of transformer models, we introduce a novel method named Multivariate Time-Series Imputation with Transformers (MTSIT). This entails an unsupervised autoencoder model featuring a transformer encoder, leveraging unlabeled observed data for simultaneous reconstruction and imputation of multivariate time-series.

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Unlocking Real-Time 3D Imaging with Single-Photon LiDAR in Challenging Environments

By: 
Dr. Abderrahim Halimi

Our method overcomes 3D underwater imaging challenges by offering high-frame-rate video 3D imaging (>100 fps), providing uncertainty measures for estimates, and extending applicability to various obscurant media imaging.

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PANNs: Large-Scale Pretrained Audio Neural Networks for Audio Pattern Recognition

By: 
Dr. Qiuqiang Kong

Pretrained audio neural networks (PANNs) are trained on 5800 hours of AudioSet data that can be used to recognize hundreds of sound types in the natural world.

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