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Reversible data hiding of a VQ index table based on referred counts

JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION 2009年第6期20卷 399-407页

作者： Yang, Cheng-Hsing Lin, Yi-Cheng Natl Pingtung Univ Educ Dept Comp Sci Pingtung 900 Taiwan

This paper presents a new reversible VQ-based hiding scheme that can recover the original VQ compressed codes after data extraction. Our scheme sorts a VQ codebook using the referred counts. The VQ codebook is then divided into 2(B) clusters and half of these clusters are used to embed secret data, in which B denotes the size of the secret data embedded into each VQ index. Compared to Chang et al.'s scheme, which divides a sorted VQ codebook into 2(B-1) x 3 clusters and uses the front one-third clusters to embed secret data, our method can embed more data. Moreover, indicator, index exchanging, and side-match prediction schemes are proposed to further improve our scheme. Under the same sorted VQ codebook, the experimental results demonstrate that our data hiding algorithm has higher capacities and better compression rates. (C) 2009 Elsevier Inc. All rights reserved.

关键词： Data hiding Reversible embedding Vector quantization Codebook clustering Lossless compression Steganography Side-match predictive coding

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Unequal error protection for real-time video in mobile ad hoc networks via multi-path transport

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COMPUTER COMMUNICATIONS 2007年第17期30卷 3293-3306页

作者： El Al, Ahmed Abd Saadawi, Tarek Lee, Myung Sonus Networks Westford MA 01886 USA CUNY Dept Elect Engn New York NY 10031 USA

In this paper, we propose a mechanism that combines retransmission-based error control with multi-path transport (MPT), to provide different levels of protection to real-time video in ad hoc networks. The mechanism factors in the importance of the retransmitted packets to the reconstructed video quality as well as the end-to-end latency constraints to minimize the overhead and maximize the reconstructed video quality at the receiver. Simulation results show that the proposed retransmission mechanism maintains the video quality under different loss rates and mobility speeds, with less overhead compared to error control methods that depend on controlling the intra-update rate. In addition, the mechanism is shown to be more robust to wireless losses and mobility than schemes that combine layered and multiple description coding with multi-path transport. (c) 2007 Elsevier B.V. All rights reserved.

关键词： unequal error protection multi-path transport predictive coding video transport over ad hoc networks

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Efficient Shape coding for Object-Based 3D Video Applications

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2019年第11期29卷 3317-3325页

作者： Zhu, Zhongjie Wang, Yuer Jiang, Gangyi Yang, Yueping Zhejiang Wanli Univ Ningbo Key Lab DSP Ningbo 315100 Zhejiang Peoples R China Ningbo Univ Inst Circuits & Syst Ningbo 315211 Zhejiang Peoples R China Ningbo Power Supply Co State Grid Corp China Ningbo 315000 Zhejiang Peoples R China

Shape is a popular way to define objects and shape coding is a key technique for object-based 3D video applications. In this paper, the issue of efficient shape coding for object-based 3D video applications is addressed, and a novel contour-based and chain-represented scheme is proposed. For a given 3D shape video, contour extraction and preprocessing are first implemented followed by chain-based representation. Then, to achieve high coding efficiency, a chain-based prediction and compensation technique is developed based on joint motion-compensated prediction and disparity-compensated prediction to effectively exploit the intra-view temporal correlation and the inter-view spatial correlation. Experiments are conducted, and the results demonstrate that the proposed scheme is more efficient than the existing methods, including state-of-the-art methods.

关键词： Shape Encoding Three-dimensional displays Image coding Correlation Video coding Video sequences 3D video shape coding contour-based coding predictive coding

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Allostasis as a core feature of hierarchical gradients in the human brain

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NETWORK NEUROSCIENCE 2022年第4期6卷 1010-1031页

作者： Katsumi, Yuta Theriault, Jordan E. Quigley, Karen S. Barrett, Lisa Feldman Massachusetts Gen Hosp Dept Neurol Boston MA 02114 USA Harvard Med Sch Boston MA 02115 USA Northeastern Univ Dept Psychol Boston MA 02115 USA Massachusetts Gen Hosp Dept Psychiat Boston MA 02114 USA Massachusetts Gen Hosp Athinoula A Martinos Ctr Biomed Imaging Boston MA 02114 USA

Author Summary Allostasis refers to the process by which the brain anticipates the needs of the body and attempts to meet those needs before they arise, and is one specific instantiation of a broader predictive processing framework. In this perspective article, we propose that allostasis is a basic function of the human brain subserved by an intrinsic architecture composed of two hierarchical functional gradients. Our framework, based on a synthesis of multimodal and multiscale evidence across species, begins to sketch a coherent, neurobiologically inspired research program suggesting that predictive energy regulation is at the core of human brain function, and by extension, psychological and behavioral phenomena, providing a shared vocabulary for theory building and knowledge accumulation. This paper integrates emerging evidence from two broad streams of scientific literature into one common framework: (a) hierarchical gradients of functional connectivity that reflect the brain's large-scale structural architecture (e.g., a lamination gradient in the cerebral cortex);and (b) approaches to predictive processing and one of its specific instantiations called allostasis (i.e., the predictive regulation of energetic resources in the service of coordinating the body's internal systems). This synthesis begins to sketch a coherent, neurobiologically inspired framework suggesting that predictive energy regulation is at the core of human brain function, and by extension, psychological and behavioral phenomena, providing a shared vocabulary for theory building and knowledge accumulation.

关键词： predictive processing predictive coding Active inference Interoception Functional networks Energetics

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Learning-Free Hyperspectral Anomaly Detection With Unpredictive Frequency Residual Priors

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IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 2022年 15卷 6294-6305页

作者： Zhou, Shichao Wang, Wenzheng Gao, Chentao Beijing Informat Sci & Technol Univ Key Lab Informat & Commun Syst Minist Informat Ind Beijing 100192 Peoples R China Beijing Inst Technol Sch Informat & Elect Beijing 100081 Peoples R China

Hyperspectral anomaly detection aims to fast and credibly find nontrivial candidate targets without prior knowledge, which has become an increasingly pressing need as imagery swath and resolution are growing rapidly. Relevant state-of-the-art learning-based anomaly detection approaches have benefited from data-driven hierarchical feature embeddings that typically model the geometric distribution of spectral vectors. However, most of these techniques are incompatible with resource-constrained applications: 1) huge computational costs caused by feedforward convolution operation cannot be supported with limited computation resources and storage (e.g., in-orbit processing);2) detection accuracy relies on large-scale training datasets, which results in labor-expensive imagery collection, pixel-level labeling, and time-consuming learning procedure. To address these issues, we advocate a learning-free, frequency domain anomaly detection method combined with predictive coding, an intriguing heuristic prior from human vision system. Technically, 1) inherently efficient frequency transformation could be implemented with existing image compression modules (e.g., JPEG or JPEG2000 codec), which improves the utilization of computational resources;2) predictive coding mechanism is exploited for suppressing frequently occurring information represented in the low-entropy frequency domain, such that the "unpredictive" subject (i.e., anomaly spectrums) can "pop out" with naive residuals. Such heuristic prior incorporated into the computational model can reduce dependence on the large-scale training set. Experiments on real-world hyperspectral datasets confirm the efficacy of our model. Besides, low computation cost of the proposed (fast frequency transformation and analytical solutions) anomaly detector facilitates rather straightforward sliding window verification in high-resolution imagery.

关键词： Anomaly detection Hyperspectral imaging Computational modeling Image reconstruction Frequency-domain analysis Training Image coding Fast detection hyperspectral frequency domain analysis learning-free anomaly detection predictive coding

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A New Encoder for Continuous-Time Gaussian Signals With Fixed Rate and Reconstruction Delay

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2012年第6期60卷 3052-3064页

作者： Marelli, Damian Mahata, Kaushik Fu, Minyue Univ Newcastle Sch Elect Engn & Comp Sci Callaghan NSW 2308 Australia Zhejiang Univ Dept Control Sci & Engn Hangzhou Zhejiang Peoples R China

In this paper, we propose a method for encoding continuous-time Gaussian signals subject to a usual data rate constraint and, more importantly, a reconstruction delay constraint. We first apply a Karhunen-Loeve decomposition to reparameterize the continuous-time signal as a discrete sequence of vectors. We then study the optimal recursive quantization of this sequence of vectors. Since the optimal scheme turns out to have a very cumbersome design, we consider a simplified method, for which a numerical example suggests that the incurred performance loss is negligible. In this simplified method, we first build a state space model for the vector sequence and then use Bayessian tracking to sequentially encode each vector. The tracking task is performed using particle filtering. Numerical experiments show that the proposed approach offers visible advantages over other available approaches, especially when the reconstruction delay is small.

关键词： Bayesian methods continuous-time signals particle filters predictive coding quantization state-space methods transform coding

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Revealing the Computational Meaning of Neocortical Interarea Signals

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FRONTIERS IN COMPUTATIONAL NEUROSCIENCE 2020年 14卷 74页

作者： Yamakawa, Hiroshi Univ Tokyo Tokyo Japan Whole Brain Architecture Initiat Edogawa Ku Tokyo Japan

To understand the function of the neocortex, which is a hierarchical distributed network, it is useful giving meaning to the signals transmitted between these areas from the computational viewpoint. The overall anatomical structure or organs related to this network, including the neocortex, thalamus, and basal ganglia, has been roughly revealed, and much physiological knowledge, though often fragmentary, is being accumulated. The computational theories involving the neocortex have also been developed considerably. By introducing the assumption "The signals transmitted by interarea axonal projections of pyramidal cells in the neocortex carry different meanings for each cell type, common to all areas," derived from its nature as a distributed network in the neocortex, allows us to specify the computational meanings of interarea signals. In this paper, first, the types of signals exchanged between neocortical areas are investigated, taking into account biological constraints, and employing theories such as predictive coding, reinforcement learning, representation emulation theory, and BDI logic as theoretical starting points, two types of feedforward signals (observation and deviation) and three types of feedback signals (prediction, plan, and intention) are identified. Next, based on the anatomical knowledge of the neocortex and thalamus, the pathways connecting the areas are organized and summarized as three corticocortical pathways and two thalamocortical pathways. Using this summation as preparation, this paper proposes a hypothesis that gives meaning to each type of signals transmitted in the different pathways in the neocortex, from the viewpoint of their functions. This hypothesis reckons that the feedforward corticocortical pathway transmits observation signals, the feedback corticocortical pathway transmits prediction signals, and the corticothalamic pathway mediated by core relay cells transmits deviation signals. The thalamocortical pathway, which is mediate

关键词： core and matrix thalamocortical circuit corticocortical circuit predictive coding emulation theory of representation BDI logic intention plan

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FRAME ADAPTIVE VECTOR QUANTIZATION FOR IMAGE SEQUENCE coding

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IEEE TRANSACTIONS ON COMMUNICATIONS 1988年第5期36卷 629-635页

作者： GOLDBERG, M SUN, HF FAIRLEIGH DICKINSON UNIV DEPT ELECT ENGNTEANECKNJ 07666

An adaptive technique for image sequence coding that is based on vector quantization is described. Each frame in the sequence is first decomposed into a set of vectors. A codebook is generated using the vectors of the first frame as the training sequence, and a label map is created by quantizing the vectors. The vectors of the second frame are then used to generate a new codebook, starting with the first codebook as seeds. The updated codebook is then transmitted. At the same time, the label map is replenished by coding the position and the new values of the labels that have changed from one frame to the other. The process is repeated for subsequent frames. Experimental results for a test sequences demonstrate that the technique can track the changes and maintain a nearly constant distortion over the entire sequence.< >

关键词： Vector quantization Image sequences Image coding Sun Transform coding Clustering algorithms Testing Data compression predictive coding Trajectory

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Low complexity video encoding with one-bit transform based network-driven motion estimation

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IEEE TRANSACTIONS ON CONSUMER ELECTRONICS 2007年第2期53卷 601-608页

作者： Oh, Hwa-Yong Erturk, Sarp Chang, Tae-Gyu Chung Ang Univ Sch Elect & Elect Engn IITA Professorship Program Seoul 156756 South Korea Kocaeli Univ Dept Elect & Telecommun Engn TR-41040 Kocaeli Turkey

Low complexity video encoding is desired in many applications requiring real-time encoding of video, particularly for mobile equipment. In order to reduce encoding complexity without much sacrifice in visual quality, some of the complexity can typically be shifted to the decoder, or the network. infrastructure can take part in the process by performing some encoding and/or decoding tasks. In this paper a new hybrid video coding scheme is proposed that utilizes the standard motion compensated predictive coding architecture and uses one-bit transform (1BT) representations of video frames to facilitate remote motion estimation, The one-bit transform of each video frame is computed at the encoder using low complexity operations and sent to the decoder or network infrastructure, after entropy encoding, for motion estimation. After motion estimation is carried out remotely, the motion vectors are sent back to the encoder for motion compensated predictive coding. In order to reduce the overhead introduced by one-bit transforms, differential encoding of 1BTs is also investigated. The proposed approach can provide low complexity motion compensated predictive video encoding by shifting the high computational load of motion estimation to the decoder or network infrastructure(1).

关键词： one-bit transform motion compensated predictive coding low-complexity video encoding network driven motion estimation

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A review on neural network models of schizophrenia and autism spectrum disorder

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NEURAL NETWORKS 2020年 122卷 338-363页

作者： Lanillos, Pablo Oliva, Daniel Philippsen, Anja Yamashita, Yuichi Nagai, Yukie Cheng, Gordon Radboud Univ Nijmegen Donders Inst Brain Cognit & Behav Nijmegen Netherlands Tech Univ Munich Inst Cognit Syst Arcisstr 21 Munich Germany Univ Tokyo Int Res Ctr Neurointelligence Bunkyo Ku 7-3-1 Hongo Tokyo Japan Natl Ctr Neurol & Psychiat Dept Funct Brain Res 4-1-1 Ogawa Higashi Kodaira Tokyo Japan

This survey presents the most relevant neural network models of autism spectrum disorder and schizophrenia, from the first connectionist models to recent deep neural network architectures. We analyzed and compared the most representative symptoms with its neural model counterpart, detailing the alteration introduced in the network that generates each of the symptoms, and identifying their strengths and weaknesses. We additionally cross-compared Bayesian and free-energy approaches, as they are widely applied to model psychiatric disorders and share basic mechanisms with neural networks. Models of schizophrenia mainly focused on hallucinations and delusional thoughts using neural dysconnections or inhibitory imbalance as the predominating alteration. Models of autism rather focused on perceptual difficulties, mainly excessive attention to environment details, implemented as excessive inhibitory connections or increased sensory precision. We found an excessively tight view of the psychopathologies around one specific and simplified effect, usually constrained to the technical idiosyncrasy of the used network architecture. Recent theories and evidence on sensorimotor integration and body perception combined with modern neural network architectures could offer a broader and novel spectrum to approach these psychopathologies. This review emphasizes the power of artificial neural networks for modeling some symptoms of neurological disorders but also calls for further developing of these techniques in the field of computational psychiatry. (c) 2019 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://***/licenses/by/4.0/).

关键词： Neural networks Schizophrenia Autism spectrum disorder Computational psychiatry predictive coding

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