Search · four archives
Search · four archives
19 papers · ranked by Valyu relevance
Junhao Cai, Taegun An, Chengjun Jin, Sung Il Choi + 2 more
Distributed multi-stage image compression—where visual content traverses multiple processing nodes under varying quality requirements—poses challenges. Progressive methods enable bitstream truncation but underutilize available compute resources; successive compression repeats costly pixel-domain operations and suffers…
Yujun Huang, Bin Chen, Shiyu Qin, Jiawei Li + 3 more
'Shu‐Tao Xia'] Beyond achieving higher compression efficiency over classical image compression codecs, deep image compression is expected to be improved with additional side information, e.g., another image from a different perspective of the same scene. To better utilize the side information under the distributed…
Enmao Diao, Jie Ding, Vahid Tarokh
We propose a new architecture for distributed image compression from a group of distributed data sources. The work is motivated by practical needs of data-driven codec design, low power consumption, robustness, and data privacy. The proposed architecture, which we refer to as Distributed Recurrent Autoencoder for…
Chong Han, Songtao Zhang, Biao Zhang, Jian Zhou + 1 more
As an emerging technology, edge computing will enable traditional sensor networks to be effective and motivate a series of new applications. Meanwhile, limited battery power directly affects the performance and survival time of sensor networks. As an extension application for traditional sensor networks, the energy…
Vijayaraghavan Thirumalai, Pascal Frossard
—The distributed representation of correlated multiview images is an important problem that arise in vision sensor networks. This paper concentrates on the joint reconstruction problem where the distributively compressed correlated images are jointly decoded in order to improve the reconstruction quality of all the…
Xing Xu, Zahaib Akhtar, Wyatt Lloyd, Antonio Ortega + 1 more
'Ramesh Govindan'] Abstract—The popularity of photo sharing services has increased dramatically in recent years. Increases in users, quantity of photos, and quality/resolution of photos combined with the user expectation that photos are reliably stored indefinitely creates a growing burden on the storage backend of…
Kumar Viswanatha, Sharadh Ramaswamy, Ankur Saxena, Emrah Akyol + 1 more
'Kenneth Rose'] This paper considers the problem of distributed source coding for a large network. A major obstacle that poses an existential threat to practical deployment of conventional approaches to distributed coding is the exponential growth of the decoder complexity with the number of sources and the encoding…
Conghuan Ye, Shenglong Tan, Zheng Wang, Binghua Shi + 2 more
'Congxu Zhu'] With the advent of cloud computing and social multimedia communication, more and more social images are being collected on social media platforms, such as Facebook, TikTok, Flirk, and YouTube. The amount of social images produced and disseminated is rapidly increasing. Meanwhile, cloud computing-assisted…
Bin Duan, Logan A Walker, Bin Xie, Wei Jie Lee + 3 more
Recent advances in microscopy have pushed imaging data generation to an unprecedented scale. While scientists benefit from higher spatiotemporal resolutions and larger imaging volumes, the increasing data size presents significant storage, visualization, sharing, and analysis challenges. Lossless compression typically…
Daniel G. Costa, Luiz Affonso Guedes
Visual sensor networks (VSNs) comprised of battery-operated electronic devices endowed with low-resolution cameras have expanded the applicability of a series of monitoring applications. Those types of sensors are interconnected by ad hoc error-prone wireless links, imposing stringent restrictions on available…
Gail McConnell
Microscopy datasets are often spatially sparse, wherein relevant structures occupy only a small fraction of the total field of view (FOV), leaving large regions of background devoid of signal. This inherent inefficiency creates file sizes that are larger than needed, which increases the time needed for computational…
Luke Staniscia, Yun William Yu
Because of the rapid generation of data, the study of compression algorithms to reduce storage and transmission costs is important to bioinformaticians. Much of the focus has been on sequence data, including both genomes and protein amino acid sequences stored in FASTA files. Current standard practice is to use an…
Le Dong, Zhiyu Lin, Yan Liang, Ling He + 4 more
'Xiaochun Cao' 'Ebroul lzquierdo'] Abstract—This paper introduces an effective processing framework nominated ICP (Image Cloud Processing) to powerfully cope with the data explosion in image processing field. While most previous researches focus on optimizing the image processing algorithms to gain higher efficiency…
Yifan Ma, Chengqiang Yi, Yao Zhou, Zhaofei Wang + 9 more
With the rapid development in advanced imaging techniques, massive image data have been acquired for various biomedical applications, posing significant challenges to their efficient storage, transmission, and sharing. Classical model-or learning-based compression algorithms are optimized for specific dimensional data…
Edward T. Eng, Mykhailo Kopylov, Carl J. Negro, Sarkis Dallaykan + 5 more
Recent advances in instrumentation and software for cryoEM have increased the applicability and utility of this method. Coupled with the adoption of automated pipelines, significant infrastructure support is required to sustain high throughput workflows. In particular, data generation rates may outpace the ability to…
Metin Aktas, Murat Kuscu, Ergin Dinc, Ozgur B. Akan + 1 more
'Kim-Kwang Raymond Choo'] Spatial correlation between densely deployed sensor nodes in a wireless sensor network (WSN) can be exploited to reduce the power consumption through a proper source coding mechanism such as distributed source coding (DSC). In this paper, we propose the Decoding Delay-based Distributed Source…
Victoria Erofeeva, Oleg Granichin, Vikentii Pankov, Zeev Volkovich + 1 more
'Ayesha Maqbool'] The paper presents a decentralized, real-time clustering method designed for large-scale, distributed environments such as the Internet of Things (IoT). The approach combines compressed sensing for dimensionality reduction with a consensus protocol for distributed aggregation, enabling each node to…
Ijaz Ahmad, Seokjoo Shin, Kuo-Liang Chung
Perceptual encryption (PE) of images protects visual information while retaining the intrinsic properties necessary to enable computation in the encryption domain. Block-based PE produces JPEG-compliant images with almost the same compression savings as that of the plain images. The methods represent an input color…
Maxim Lippeveld, Daniel Peralta, Andrew Filby, Yvan Saeys
Due to high resolution and throughput of modern image cytometry platforms, morphologically profiling generated datasets poses a significant computational challenge. Here, we present Scalable Cytometry Image Processing (SCIP), an image processing software aimed at running on distributed high performance computing…