12 papers · ranked by Valyu relevance
Yuhang Wang, Weihua Chen, Linjing Song, Zhiping Xu + 6 more
With the rapid growth of data volume in sensor networks, lossy source coding systems achieve high-efficiency data compression with low distortion under limited transmission bandwidth. However, conventional compression algorithms rely on a two-stage framework with high computational complexity and frequently struggle to…
Ali Hussein, Jun Chen, Chao Tian, S. Sandeep Pradhan
Perception-aware lossy source coding has attracted significant recent interest. It augments the classical distortion criterion with an explicit perception constraint, thereby enabling more refined control over fidelity and perceptual quality. Despite rapid progress, the diversity of rate-distortion-perception…
Tao Guo, Zhangyao Song, Huihui Wu, Yang Li + 1 more
This paper analyzes the semantic rate-distortion problem motivated by task-oriented data compression with side information. The semantic information related to a task is not directly accessible to the encoder but implicitly impacts the observations through a joint probability distribution. The decoder aims to…
Duong, Thien T., Springer, Jan P.
Perceptual quality of audio is the combination of aural accuracy and listener-perceived sound fidelity. It is how humans respond to the accuracy, intelligibility, and fidelity of aural media. Today this fidelity is also heavily influenced by the use of audio compression codecs for storing aural media in digital form.…
Christine Beavers, Herbert J. Bernstein, Aaron S. Brewster, Max Burian + 19 more
This paper is a report of the High Data Rate Macromolecular Crystallography workshop held on 23 July 2025 as part of the 2025 meeting of the American Crystallographic Association in Lombard, IL, USA, 18-23 July 2025. This report summarizes the discussions, questions, action items, and recommendations that arose from…
Alin-Adrian Alecu, Mohammad Ali Tahouri, Adrian Munteanu, Bujor Păvăloiu + 1 more
Near-lossless coding schemes traditionally rely on uniform quantization to control the maximum absolute error ( $L_{\infty}$ norm) of residual signals, often assuming a parametric model for the source distribution. This paper introduces a novel design framework for non-uniform, entropy-aware $L_{\infty}$-oriented…
Mohsen Jenadeleh, Jon Sneyers, João Ascenso, Thomas Richter + 7 more
Recent advances in conventional and learning-based image coding have increased the demand for benchmark datasets that support fine-grained assessment of compressed image quality, particularly for learning-based image compression methods. This paper introduces Assessment of Image Coding 2026 (AIC2026), a large-scale…
Yichen Wang, Yijie Lin, Ching-Chun Chang, Chin-Chen Chang + 2 more
With the rapid advancement of the Internet of Medical Things (IoMT), the efficient transmission and management of large-scale medical images in bandwidth- and resource-constrained networks remain critical challenges. This paper proposes a high-payload data hiding method in Absolute Moment Block Truncation Coding…
Xiangbo Wang, W. Jiang, Jin Wang, Yubo You + 2 more
Recent neural audio compression models often rely on residual vector quantization for high-fidelity coding, but using a fixed number of per-frame codebooks is suboptimal for the wide variability of audio content—especially for signals that are either very simple or highly complex. To address this limitation, we propose…
Han, Zhuohang, Dai, Jincheng + 12 more
—Real-time speech communication over wireless networks remains challenging, as conventional channel protection mechanisms cannot effectively counter packet loss under stringent bandwidth and latency constraints. Semantic communication has emerged as a promising paradigm for enhancing the robustness of speech…
Tiberio Uricchio, Marco Bertini
While neural lossless image compression has advanced significantly with learned entropy models, lossless video compression remains largely unexplored in the neural setting. We present NeuralLVC, a neural lossless video codec that combines masked diffusion with an I/P-frame architecture for exploiting temporal…
Ya Liu, Rui Zhang, Yong Zhang, Yuwei Chen + 1 more
Large field-of-view (FOV) infrared imaging, widely utilized in applications including target detection and remote sensing, generates massive datasets that pose significant challenges for transmission and storage. To address this issue, we propose an efficient lossless compression method for large FOV infrared video.…