Article
Computer Science, Artificial Intelligence
Anabeth P. Radunz, Fabio M. Bayer, Renato J. Cintra
Summary: The paper introduces a new class of low-complexity transforms obtained through applying the round function to KLT matrix elements, which perform well in image compression with low implementation cost.
JOURNAL OF REAL-TIME IMAGE PROCESSING
(2022)
Article
Computer Science, Artificial Intelligence
Tassnim Dardouri, Mounir Kaaniche, Amel Benazza-Benyahia, Jean-Christophe Pesquet
Summary: This paper proposes a compression scheme based on neural network learning of lifting operators, and improves the dynamic fully connected neural network model for better consideration of input images. The experimental results demonstrate the advantages of this method in lossy and lossless image compression.
IEEE TRANSACTIONS ON IMAGE PROCESSING
(2022)
Article
Computer Science, Interdisciplinary Applications
Diego Rossinelli, Gilles Fourestey, Felix Schmidt, Bjoern Busse, Vartan Kurtcuoglu
Summary: The rapid increase in medical and biomedical image acquisition rates has created new opportunities and challenges for image analysis. Development of data compression schemes has become an important step in addressing the high I/O bandwidth demand caused by high acquisition rates.
IEEE TRANSACTIONS ON MEDICAL IMAGING
(2021)
Article
Engineering, Electrical & Electronic
Anabeth P. Radunz, Thiago L. T. da Silveira, Fabio M. Bayer, Renato J. Cintra
Summary: This work proposes low-computational cost approximations for the KLT that are suitable for image and video compression. Extensive computational experiments on blocklengths of 4, 8, 16, and 32 demonstrate the effectiveness of these low-complexity transforms.
SIGNAL PROCESSING-IMAGE COMMUNICATION
(2022)
Article
Computer Science, Information Systems
Jin Young Lee, The Van Le, Yongho Choi, Kiho Choi
Summary: This paper proposes a low-complexity two-step lossless depth coding method for transmitting depth images in a limited bandwidth. The method achieves reductions in both encoding complexity and bitrate.
MULTIMEDIA TOOLS AND APPLICATIONS
(2022)
Article
Chemistry, Multidisciplinary
Tie Zheng, Yuqi Dai, Changbin Xue, Li Zhou
Summary: This study proposes a prediction-based compression scheme for hyperspectral images, which significantly reduces the image size by removing redundant information, and analyzes the optimal number of prediction bands through experiments.
APPLIED SCIENCES-BASEL
(2022)
Article
Geosciences, Multidisciplinary
Yonggao Yue, Zhiyuan Wu, Shusheng Wang, Lei Wan, Panfeng Wang, Xiaohan Yang, Yinghao Cui, Kai Zhang, Lijuan Deng
Summary: Before constructing a tunnel, it is necessary to utilize advanced prospecting techniques to detect unexpected geological heterogeneity. This paper introduces the Karhunen-Loeve beamforming method to extract lateral signals from the tunnel, improving the quality of the target signals.
JOURNAL OF APPLIED GEOPHYSICS
(2023)
Article
Telecommunications
Monika Sharma, Mantosh Biswas
Summary: The paper introduces a Collaborative Representation based K Closest Neighbor classes (CRKCN) classification algorithm that shows promising improvements in classification performance for hyperspectral images compared to traditional methods.
WIRELESS PERSONAL COMMUNICATIONS
(2022)
Article
Engineering, Electrical & Electronic
Joao M. Santos, Lucas A. Thomaz, Pedro A. A. Assuncao, Luis A. da Silva Cruz, Luis M. N. Tavora, Sergio M. M. Faria
Summary: This paper proposes a lossless light field codec called hierarchical Minimum Rate Predictors (H-MRP), which provides scalability and random access capabilities for lossless compression of light field data.
SIGNAL PROCESSING-IMAGE COMMUNICATION
(2022)
Article
Geochemistry & Geophysics
Miguelm Hernandez-Cabronero, Aaron Barry Kiely, Matthew Klimesh, Ian Blanes, Jonathan Ligo, Enrico Magli, Joan Serra-Sagrista
Summary: The Consultative Committee for Space Data Systems (CCSDS) has published a new image compression standard that supports near-lossless compression through closed-loop quantization of prediction errors and includes a new hybrid entropy coder for enhanced compression performance. This standard allows significantly smaller compressed data volumes compared to the previous version, while controlling the quality of decompressed images.
IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE
(2021)
Article
Geochemistry & Geophysics
Vijay Joshi, J. Sheeba Rani
Summary: This study proposes a new lossless algorithm for on-board satellite hyperspectral data compression, which utilizes spectral and spatial correlation and has lower computational complexity. Non-binary tree traversal and nearest neighbor method are used with neighbor-driven decision-making in the pre-processing stage. The algorithm shows reduced computational complexity and lesser data dependencies compared to the CCSDS 123.0-B-1 standard, with comparable compression performance to other state-of-the-art on-board LS compression methods.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2023)
Article
Geochemistry & Geophysics
Reetu Hooda, W. David Pan
Summary: The proposed scheme achieves high compression ratios by partitioning the intricate regions of the image into smaller blocks in a novel way; an analysis of the low-order linear predictive model's effect on the original image is conducted, showing lower-entropy residual images that improve compression efficiency; an optimization algorithm is used to find the best combination of scan directions for nonzero blocks, demonstrating improved compression efficiency with additional iterations in simulation results.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2022)
Article
Acoustics
Antoine Baudiquez, Eric Lantz, Enrico Rubiola, Francois Vernotte
Summary: This article discusses the measurement of the power spectrum of red noise processes at the lowest frequencies, highlighting the need for averaging simultaneous observations from multiple instruments. It compares the Bayesian confidence interval of the red noise parameter using two estimators, the spectrum average and the cross-spectrum. The study finds that the spectrum average is slightly more efficient than the cross-spectrum, but recommends using both estimators to account for notable differences in their upper limits.
IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL
(2022)
Article
Chemistry, Analytical
Daniele Tosi, Zhannat Ashikbayeva, Aliya Bekmurzayeva, Zhuldyz Myrkhiyeva, Aida Rakhimbekova, Takhmina Ayupova, Madina Shaimerdenova
Summary: Optical fiber ball resonators based on single-mode fibers in the infrared range are an emerging technology for refractive index sensing and biosensing. These devices are easy and rapid to fabricate and can be functionalized for biosensing. While the spectral response of these devices is poorly correlated with their size and shape, a detection method based on Karhunen-Loeve transform can accurately detect the response of the ball resonator in any working condition.
Article
Computer Science, Information Systems
Chao Yang, Xinfeng Zhang, Ping An, Liquan Shen, C. -C. Jay Kuo
Summary: In this work, an unsupervised feature extraction approach based on Karhunen-Loeve transform (KLT) for blind image quality assessment (BIQA) is proposed. A normalization operation and KLT are used to extract image structural features, with generalized Gaussian distribution employed to model the KLT coefficients distribution as quality relevant features. Extensive experiments show that the proposed method outperforms existing BIQA methods in terms of agreement with human subjective scores on various types of distortions.
IEEE TRANSACTIONS ON MULTIMEDIA
(2021)
Article
Geochemistry & Geophysics
Naoufal Amrani, Joan Serra-Sagrista, Pascal Peter, Joachim Weickert
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2017)
Article
Geochemistry & Geophysics
Joan Bartrina-Rapesta, Ian Blanes, Francesc Auli-Llinas, Joan Serra-Sagrista, Victor Sanchez, Michael W. Marcellin
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2017)
Article
Geochemistry & Geophysics
Joaquin Garcia-Sobrino, Joan Serra-Sagrista, Valero Laparra, Xavier Calbet, Gustau Camps-Valls
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2017)
Article
Remote Sensing
I. Blanes, M. Albinet, R. Camarero, J. Serra-Sagrista
INTERNATIONAL JOURNAL OF REMOTE SENSING
(2018)
Article
Remote Sensing
Sara Alvarez-Cortes, Naoufal Amrani, Miguel Hernandez-Cabronero, Joan Serra-Sagrista
INTERNATIONAL JOURNAL OF REMOTE SENSING
(2018)
Article
Remote Sensing
Sara Alvarez-Cortes, Naoufal Amrani, Joan Serra-Sagrista
INTERNATIONAL JOURNAL OF REMOTE SENSING
(2018)
Article
Chemistry, Analytical
Joaquin Garcia-Sobrino, Joan Serra-Sagrista, Joan Bartrina-Rapesta
Article
Geochemistry & Geophysics
Sara Alvarez-Cortes, Joan Bartrina-Rapesta, Joan Serra-Sagrista
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2018)
Article
Computer Science, Interdisciplinary Applications
Miguel Hernandez-Cabronero, Victor Sanchez, Ian Blanes, Francesc Auli-Llinas, Michael W. Marcellin, Joan Serra-Sagrista
IEEE TRANSACTIONS ON MEDICAL IMAGING
(2019)
Article
Computer Science, Information Systems
Miguel Hernandez-Cabronero, Michael W. Marcellin, Ian Blanes, Joan Serra-Sagrista
IEEE TRANSACTIONS ON MULTIMEDIA
(2018)
Article
Environmental Sciences
Ian Blanes, Aaron Kiely, Miguel Hernandez-Cabronero, Joan Serra-Sagrista
Article
Geochemistry & Geophysics
Joaquin Garcia-Sobrino, Valero Laparra, Joan Serra-Sagrista, Xavier Calbet, Gustau Camps-Valls
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2019)
Article
Computer Science, Information Systems
Ian Blanes, Miguel Hernandez-Cabronero, Joan Serra-Sagrista, Michael W. Marcellin
Article
Computer Science, Information Systems
Joan Bartrina-Rapesta, Michael W. Marcellin, Joan Serra-Sagrista, Miguel Hernandez-Cabronero
Proceedings Paper
Computer Science, Theory & Methods
Manuel Martinez, Joan Serra-Sagrista
2019 DATA COMPRESSION CONFERENCE (DCC)
(2019)