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Probing the Single-Event Sensitivity of a COTS 3D-Integrated Imager With Alpha Particle Irradiation

IEEE TRANSACTIONS ON NUCLEAR SCIENCE 2023年第4期70卷 410-417页

作者： Hu, M. D. Padgett III, F. McCurdy, M. W. Sierawski, B. D. Schrimpf, R. D. Reed, R. A. Alles, M. L. Vanderbilt Univ Dept Elect & Comp Engn Nashville TN 37235 USA

The single-event response of a three-layer heterogeneously integrated commercial off-the-shelf (COTS) CMOS image sensor (CIS) to alpha particles of different energies is analyzed. The energies of the alpha particles are selected, such that they stop in two separate functional layers of the device-under-test (DUT). Differences in the single-event response of the DUT depend on alpha particle energy. Spatial profiling of ionizing events reveals susceptibility in the peripheral circuitry of the dynamic random-access memory (DRAM) layer to single-event functional interrupts (SEFIs). The on-chip demosaicing algorithm contributes significantly to the number of pixels affected by transient-ionizing events. Large groupings of affected pixels are manifestations of ionizing events in the peripheral circuitry contained within the image-sensitive layer of the DUT. Similarities in the captured data sets reveal the single-event response of the pixel layer dominates the system-level response of the DUT.

关键词： Alpha particles Standards Random access memory Radiation effects Indexes Image color analysis transform coding 3D-integrated circuit (IC) alpha particle irradiation CMOS image sensor (CIS) commercial off-the-shelf (COTS) radiation effects single-event effect (SEE) single-event latchup (SEL) single-event transient (SET) single-event upset (SEU) stacked IC

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Low Complexity and Low Memory Compression Algorithm for Hyperspectral Image Sensors

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WIRELESS PERSONAL COMMUNICATIONS 2023年第2期131卷 805-833页

作者： Bajpai, Shrish Integral Univ Fac Engn & Informat Technol Elect & Commun Engn Dept Lucknow Uttar Pradesh India

The 3D-zero memory set partitioned embedded block (3D-ZM-SPECK) is an embedded and memory-efficient compression algorithm. Through, the 3D-ZM-SPECK does not require any coding memory, but testing of the sets for each bit-plane increases the complexity significantly which led a big constrain for the low resource HS image sensors. The proposed HS image compression algorithm is the low complexity solution of 3D-ZM-SPECK which reduces the recursive significance test of sets. Simulation results demonstrate that the proposed 3D-M-ZM-SPECK significantly reduces the complexity by similar to 25% with the other state of art HS image compression algorithms. Thus, it is a viable option for the HS image sensors.

关键词： transform coding Hyperspectral data compression Image coding Rate-distortion Complexity

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Solution to secure data and decision at sensor nodes and communication links of smart grid networks using blockchain and IPFS

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JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2023年第3期45卷 3701-3714页

作者： Muthulakshmi, S. Chitra, R. Noorul Islam Ctr Higher Educ Dept Comp Sci & Engn Thuckalay India Karunya Inst Technol & Sci Dept Comp Sci & Engn Coimbatore Tamil Nadu India

Smart grid is proposed as a solution to the problems of production, distribution, monitoring, and control of the electricity in traditional power grids. Smart grid networks place IoT sensor nodes at various grid lines and collect large volume of data about power flow, usage etc. The collected data are analyzed for various applications like demand forecasting, fault diagnosis and fault prediction etc. The sensor nodes and the communication links can be compromised affecting the privacy of consumers. False data can be propagated with malicious intentions. This work proposes a secure and privacy preserving framework for smart grid IoT networks to secure the data and decision at sensor nodes and communication links. The work proposes a novel Data and Decision rules Secure Efficient Smart Grid (DDSESG) framework integrating secure compressive sensing technique with blockchain and interplanetary file system (IPFS) for securing both data and decision. Through experimental analysis, the proposed solution is found to provide higher resiliency against data security attacks at comparative 12.4% lower computation cost, 15% lower communication cost, 19.9% lower storage cost. Forecasting on transformed data in proposed solution had only a marginal 1.08% difference in accuracy compared to forecasting on original data.

关键词： Internet of things blockchain IPFS smart grid compressive sensing transform coding

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The 3/4 Conjecture for Fix-Free Codes With at Most Three Distinct Codeword Lengths

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IEEE TRANSACTIONS ON INFORMATION THEORY 2023年第3期69卷 1452-1485页

作者： Congero, Spencer Zeger, Kenneth Univ Calif San Diego Dept Elect & Comp Engn La Jolla CA 92093 USA

The 3/4 conjecture was posed 25 years ago by Ahlswede, Balkenhol, and Khachatrian, and states that if a multiset of positive integers has Kraft sum at most 3/4, then there exists a code that is both a prefix code and a suffix code with these integers as codeword lengths. We prove that the 3/4 conjecture is true whenever the given multiset of positive integers contains at most three distinct values.

关键词： Codes Upper bound Error correction codes Channel coding transform coding Standards Indexes Prefix codes Kraft inequality Huffman codes unique decodability

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Specular Detection and Rendering for Immersive Multimedia

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IEEE MULTIMEDIA 2023年第2期30卷 38-47页

作者： Van Le, The Choi, Yongho Lee, Jin Young Sejong Univ Dept Intelligent Mechatron Engn Seoul 05006 South Korea

Immersive multimedia has received a lot of attention because of its huge impact on user experience. To realize high immersion in virtual environments, many virtual views should be generated at arbitrary viewpoints with advanced display devices. However, specular regions, which affect user experience, have not been fully investigated in an immersive multimedia field. In this article, we propose specular highlight detection and rendering methods to improve immersion. For specular detection, a high-performance variational attention U-network (VAUnet), which combines a variational autoencoder and a spatial attention mechanism, is proposed with a hybrid loss function. The specular regions detected from VAUnet are compressed with an immersive video coding standard (MPEG-I), and then the rendering is performed by considering the decompressed specular regions. Extensive experiments demonstrate that the proposed method improves specular detection performance and subjective rendering quality.

关键词： Rendering (computer graphics) transform coding Feature extraction Streaming media Geometry Deep learning Immersive experience User experience Multimedia systems

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A Highly Robust Reversible Watermarking Scheme Using Embedding Optimization and Rounded Error Compensation

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2023年第4期33卷 1593-1609页

作者： Tang, Yichao Wang, Shuai Wang, Chuntao Xiang, Shijun Cheung, Yiu-Ming South China Agr Univ Coll Math & Informat Guangzhou 510642 Peoples R China Minist Agr & Rural Affairs Key Lab Smart Agr Technol Trop South China Guangzhou 510642 Peoples R China Guangzhou Key Lab Intelligent Agr Guangzhou 510642 Peoples R China Jinan Univ Coll Informat Sci & Technol Guangzhou 510632 Peoples R China Hong Kong Baptist Univ Dept Comp Sci Hong Kong Peoples R China

The robust reversible watermarking (RRW) requires high robustness and capacity on the condition of reversibility and imperceptibility, which still remains a big challenge nowadays. In this paper, we propose a two-stage RRW scheme that improves robustness and capacity through embedding optimization and rounded error compensation. The first stage inserts a robust watermark into the selected Pseudo-Zernike moments (PZMs) by using an adaptive normalization method and an optimized embedding strategy. Specifically, the adaptive normalization method achieves both an invariance to pixel amplitude variation and a balance between robustness and imperceptibility, and the optimized embedding strategy reduces embedding distortions remarkably. The watermarked PZMs are inversely transformed to generate the robustly watermarked image, in which rounded errors caused in the inverse transformation is compensated elaborately and thus a larger capacity can be obtained at the same embedding distortion. The second stage embeds a reversible watermark consisting of errors between the robust watermark embedded image and the original one, aiming at achieving the reversibility in case of no attacks. Extensive experimental simulations show that the proposed scheme provides strong robustness against common signal processing, including AWGN, salt-and-pepper noise, JPEG, JPEG2000, median filtering, mean filtering, geometrical transformations involving rotation and scaling, and a compressive sensing attack exemplified by two-dimensional compressive sensing, which outperforms the state-of-the-art schemes. Our code is available at https://***/yichao-tang/PZMs-RRW.

关键词： Watermarking Robustness transform coding Strain Distortion Copyright protection Error compensation Robust reversible watermarking compensation information Pseudo-Zernike moments geometric deformations

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Reversible Data Hiding for JPEG Images With Adaptive Multiple Two-Dimensional Histogram and Mapping Generation

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IEEE TRANSACTIONS ON MULTIMEDIA 2023年 25卷 8738-8752页

作者： Weng, Shaowei Zhou, Ye Zhang, Tiancong Xiao, Mengyao Zhao, Yao Fujian Univ Technol Fujian Prov Key Lab Big Data Min & Applicat Fuzhou 350108 Peoples R China Fujian Univ Technol Sch Elect Elect Engn & Phys Fuzhou 350108 Peoples R China Fujian Univ Technol Sch Comp Sci & Math Fuzhou 350118 Peoples R China Beijing Jiaotong Univ Inst Informat Sci Beijing 100044 Peoples R China Beijing Key Lab Adv Informat Sci & Network Technol Beijing 100044 Peoples R China

Reversible data hiding based on joint photographic experts group (JPEG) images has been extensively studied to enhance embedding performance in terms of visual quality and file size preservation at the desired payload. In this paper, an efficient adaptive RDH method for JPEG images with multiple two-dimensional (2D) histogram modification is proposed. Firstly, the proposed method proposes the block smoothness estimator and the band smoothness estimator, and then combines the two estimators to reduce the embedding distortion as much as possible at the desired payload. Instead of adopting a fixed 2D mapping or choosing one from several empirically-designed mappings for each 2D histogram, the proposed method designs an adaptive 2D mapping generation strategy to adaptively generate a large number of mappings with considering the local characteristics of histogram distribution. Since exhaustively searching for the optimal mapping achieving the highest embedding performance for each 2D histogram is time-consuming, an improved discrete particle swarm optimization is utilized in the proposed method to speed up the optimization process. Extensive experimental results also demonstrate the effectiveness of the proposed method in terms of visual quality and file size increment of the stego image.

关键词： Histograms transform coding Distortion Discrete cosine transforms Payloads Media Optimization Adaptive 2D mapping generation band smoothness estimator block smoothness estimator IDPSO JPEG images reversible data hiding

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The Discrete Cosine transform and Its Impact on Visual Compression: Fifty Years From Its Invention

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IEEE SIGNAL PROCESSING MAGAZINE 2023年第6期40卷 14-17页

作者： Wang, Yao Mukherjee, Debargha NYU Dept Elect & Comp Engn Tandon Sch Engn New York NY 11201 USA NYU Tandon Sch Engn Dept Biomed Engn New York NY 11201 USA Google Mountain View CA 94043 USA

Compression is essential for efficient storage and transmission of signals. One powerful method for compression is through the application of orthogonal transforms, which convert a group of [Formula Omitted] data samples into a group of [Formula Omitted] transform coefficients. In transform coding, the [Formula Omitted] samples are first transformed, and then the coefficients are individually quantized and entropy coded into binary bits. The transform serves two purposes: one is to compact the energy of the original [Formula Omitted] samples into coefficients with increasingly smaller variances so that removing smaller coefficients have negligible reconstruction errors, and another is to decorrelate the original samples so that the coefficients can be quantized and entropy coded individually without losing compression performance. The Karhunen–Loève transform (KLT) is an optimal transform for a source signal with a stationary covariance matrix in the sense that it completely decorrelates the original samples, and that it maximizes energy compaction (i.e., it requires the fewest number of coefficients to reach a target reconstruction error). However, the KLT is signal dependent and cannot be computed with a fast algorithm.

关键词： Visualization Technological innovation transform coding Signal processing algorithms transforms Entropy Decorrelation

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3D-Memory efficient listless set partitioning in hierarchical trees for hyperspectral image sensors

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JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2023年第6期45卷 11163-11187页

作者： Chandra, Harshit Bajpai, Shrish Alam, Monauwer Chandel, Vishal Singh Pandey, Amit Kumar Pandey, Digvijay Integral Univ Fac Engn & Informat Technol Dept Elect & Commun Engn Lucknow Uttar Pradesh India Integral Univ Fac Engn & Informat Technol Dept Elect Engn Lucknow Uttar Pradesh India Rajkiya Engn Coll Dept Appl Sci & Humanities Ambedkar Nagar Uttar Pradesh India Dr APJ Abdul Kalam Tech Univ Inst Engn & Technol Dept Tech Educ Lucknow Uttar Pradesh India

Hyperspectral (HS) images contain rich spatial and spectral information. Due to its large size, it is difficult to store, process, analyze, or transmit the critical information contained in it. The compression of hyperspectral images is inevitable. Many transform based Hyper Spectral Image Compression Algorithms (HSICAs) have been proposed in the past that work for both lossy and lossless compression processes. The transform based HSICA uses linked lists or dedicated markers or array structure to keep track of significant and insignificant sets or coefficients of a transformed HS image. However, these algorithms either suffered from low coding efficiency, high memory requirements, or high coding complexity. This work proposes a transform based HSICA using a curvelet transform to improve the directional elements and the ability to represent edges and other singularities along curves. The proposed HSICA aims to provide superior quality compressed HS images by representing HS images at different scales and directions and to achieve a high compression ratio. Experimental results show that the proposed algorithm has a low coding memory requirement with a 2% to 5% increase in coding gain compared to the other state of art compression algorithms.

关键词： Complexity theory curvelet transform hyperspectral image hyperspectral image compression transform coding

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Learned Image Compression Using Cross-Component Attention Mechanism

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IEEE TRANSACTIONS ON IMAGE PROCESSING 2023年 32卷 5478-5493页

作者： Duan, Wenhong Chang, Zheng Jia, Chuanmin Wang, Shanshe Ma, Siwei Song, Li Gao, Wen Shanghai Jiao Tong Univ Dept Comp Sci & Engn Shanghai 200240 Peoples R China Shanghai Jiao Tong Univ AI Inst Shanghai 200240 Peoples R China Chinese Acad Sci Inst Comp Technol Beijing 100190 Peoples R China Peking Univ Wangxuan Inst Comp Technol WICT Beijing 100871 Peoples R China Peking Univ Natl Engn Res Ctr Visual Technol Sch Comp Sci Beijing 100871 Peoples R China Shanghai Jiao Tong Univ Inst Image Commun & Network Engn AI Inst Shanghai 200240 Peoples R China

Learned image compression methods have achieved satisfactory results in recent years. However, existing methods are typically designed for RGB format, which are not suitable for YUV420 format due to the variance of different formats. In this paper, we propose an information-guided compression framework using cross-component attention mechanism, which can achieve efficient image compression in YUV420 format. Specifically, we design a dual-branch advanced information-preserving module (AIPM) based on the information-guided unit (IGU) and attention mechanism. On the one hand, the dual-branch architecture can prevent changes in original data distribution and avoid information disturbance between different components. The feature attention block (FAB) can preserve the important information. On the other hand, IGU can efficiently utilize the correlations between Y and UV components, which can further preserve the information of UV by the guidance of Y. Furthermore, we design an adaptive cross-channel enhancement module (ACEM) to reconstruct the details by utilizing the relations from different components, which makes use of the reconstructed Y as the textural and structural guidance for UV components. Extensive experiments show that the proposed framework can achieve the state-of-the-art performance in image compression for YUV420 format. More importantly, the proposed framework outperforms Versatile Video coding (VVC) with 8.37% BD-rate reduction on common test conditions (CTC) sequences on average. In addition, we propose a quantization scheme for context model without model retraining, which can overcome the cross-platform decoding error caused by the floating-point operations in context model and provide a reference approach for the application of neural codec on different platforms.

关键词： Image coding Context modeling transforms Decoding Standards Image reconstruction transform coding Image compression cross-component information-guided unit attention mechanism information-preserving

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