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检索条件"任意字段=4th Conference on Mathematics of Image and Data Coding, Compression, and Encryption"

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data Independent Karhunen-Loeve Transform for image and Video coding 4

Data Independent Karhunen-Loeve Transform for Image and Vide...

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IEEE 4th Information Technology and Mechatronics Engineering conference (ITOEC)

作者： Tan, Wen Liu, Xue-Dong Huang, Chuang-Ceng Wan, Jun Wuhan Univ Technol Sch Informat Engn Lab Fiber Opt Sensing Technol & Informat Proc Wuhan 430070 Hubei Peoples R China

ISBN: (纸本)9781538653739

Transform coding plays an important role in image and video compression. the Karhunen-Loeve transform (KLT) is the optimal transform for its full decorrelation ability. However, there is no general algorithm that enables its fast computation since the KLT is data dependent. Instead, the discrete cosine transform (DCT) is used widely for its good energy compaction and fast implementation algorithm. the DCT matrix can be derived by letting the correlation coefficient rho be 1 for the Markov-1 model of signal. Since such a perfectly correlated signal is rare the DCT is usually suboptimal. In this letter, taking the real image signal into consideration and setting the rho to be a value rho* closer to the actual correlation coefficient in the real image, we obtain the data independent KLT (diKLT). Experimental results show that the diKLT outperforms DCT in terms of the mean square error (MSE) and structural similarity (SSIM) as long as the rho* is big enough and the retained transform coefficients are sufficient. Although the superiority of diKLT over DCT is not prominent the advantage that a transform independent of data outperforms DCT is worthy to be noticed.

关键词： data independent discrete cosine transform Karhunen-Lo e ve transform transform coding gain transform efficiency

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Robust and secure image transmission in wireless sensor networks using enhanced compression and encryption

Robust and secure image transmission in wireless sensor netw...

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4th IASTED International conference on Advances in Computer Science and Technology, ACST 2008

作者： Mukesh, Rajeswari Damodaram, A. Bharathi, V.Subbiah Dept of Computer Science and Engg Easwari Engineering College Chennai-600 089 India JNTU College of Engineering Hyderabad-500 072 India Dean Academics DMI College of engineering Chennai-601 302 India

ISBN: (纸本)9780889867307

Security in Wireless Sensor Networks has become very much important as sensor networks are being used for sensitive applications like weather forecasting, military, medicine etc. In Wireless Sensor Network (WSN) the base station collect data from the sensor nodes and is then transmitted to the Service provider via internet. Several Imaging Sensors are also used in WSN for environmental monitoring, biomedical applications etc. image compression and image encryption are pivotal to proper storage and transmission of images in WSN. the severe resource constraints in a sensor node make it very challenging to secure sensor networks using existing strong security mechanisms. Asymmetric cryptographic algorithms are not much suitable for providing security in wireless sensor networks due to limited computation, power, and storage resources available on sensor nodes. therefore, the energyefficient security protocol proposed in this paper uses symmetric cryptographic algorithms to support security. Enhanced and energy efficient image compression and encryption proposed in this paper aims at achieving enhanced bandwidth utilization and security.

关键词： Sensor nodes

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SAR image compression Combining with Denoising Based on Multiwavelet Spatial-orientated Tree

SAR Image Compression Combining with Denoising Based on Mult...

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4th IEEE conference on Industrial Electronics and Applications

作者： Wang Ai-li Zhao Chun-hui Yang Ming-ji Harbin Engn Univ Sch Informat & Commun Engn Harbin Peoples R China Harbin Univ Sci & Technol Sch Measure Control Technol & Commun Engn Harbin Peoples R China

ISBN: (纸本)9781424427994

Synthetic aperture radar (SAR) images compression is very important in reducing the burden of data storage and transmission in relatively slow channels. the relatively new transform of multiwavelets can possess desirable features simultaneously such as short support, orthogonality and symmetry, while scalar wavelets cannot. And the spatial-orientated tree (SOT) is an efficient data structure to investigate the spatial similarity correlations among multiwavelet coefficients at different resolutions. thus a compression scheme combing speckle noise reduction based on SOT within the multiwavelet framework is proposed. At first we utilized the SOT to normalize the multiwavelet coefficients in high frequency bands and removed the signal-dependence of the speckle noise. then multiwavelet coefficients were coded to form embedded bit stream by modified set partitioning in hierarchical trees (SPIHT) algorithm. Experimental results show this coding method achieves favorable peak signal to noise ratio (PSNR) and superior speckle noise reduction performances.

关键词： image compression speckle noise multiwavelet transform spatial-orientated tree structure

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image encryption and compression Based on a VAE Generative Model 4th

Image Encryption and Compression Based on a VAE Generative M...

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4th International conference on Cloud Computing and Security (ICCCS)

作者： Duan, Xintao Liu, Jingjing Zhang, En Song, Haoxian Jia, Kai Henan Normal Univ Xinxiang 453007 Henan Peoples R China

ISBN: (纸本)9783030000127;9783030000110

To solve the problem that the network security real-time transmits image, a new image encryption and compression method based on a variational auto-encoder (VAE) generative model is proposed in this paper. the algorithm aims to encrypt and compress images by using a variational auto-encoder generative model. Firstly, we use multi-layer perceptual neural network to train the VAE model, and set parameters of the model to get the best model. then, the peak signal-to-noise ratio (PSNR) and mean square error (MSE) are used to measure the compression effect and Set the number of iterations of the model. Finally, we extract the data of based on a variational auto-encoder and perform division, then the data input the VAE generative model to encrypt image and analyze encryption images. In this paper, we use the standard image of 256 * 256 to do simulation experiments and use histogram and image correlation to analyze the results of encryption. the simulation results show that the proposed method can effectively compress and encrypt images, and then obtain better compression image than stacked auto-encoder (SAE), while the algorithm is faster and easier encrypting and decrypting images and the decrypted image distortion rate is low and suitable for practical applications.

关键词： image encryption image compression VAE Generative model

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An Improved Algorithm for Medical image compression

An Improved Algorithm for Medical Image Compression

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4th ObCom International conference on Recent Trends in Computing, Communication and Information Technology

作者： Moorthi, M. Amutha, R. SCSVM Univ Kanchipuram India SSN Coll Engn Madras Tamil Nadu India

ISBN: (纸本)9783642292156

the objective of image compression is to reduce of the image data in order to be able to store or transmit data in efficient form. One of the medical standards is the DICOM (Digital Imaging and Communications in Medicine) Standards Committee exists to create and maintain international standards for communication of biomedical diagnostic and therapeutic information in disciplines that use digital images and associated data. the important issues to be considered with the DICOM communication are memory requirement, bandwidth constraint and battery resource constraint. In the proposed method, first Segmentation is applied to get two different clusters (ROI and Non ROI). Integer Wavelet Transform based compression is applied for Higher Energy clusters and JPEG is applied for another cluster. In the reconstruction part both the reconstructed clusters are fused by fusion technique. Since Lossless and lossy compression methods are used to get high compression ratio and high quality image. Efficient edge information is obtained by using Fusion.

关键词： image compression Segmentation Integer wavelet decomposition encryption decryption decompression compression ratio

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Efficient simd acceleration of DCT and IDCT for high efficiency video coding 4

Efficient simd acceleration of DCT and IDCT for high efficie...

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4th International conference on Multimedia Technology, ICMT 2015

作者： Li, Lingyu Zhang, Xiaoyun Gao, Zhiyong Institute of Image Communication and Network Engineering Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781138027947

the promising High Efficiency Video coding (HEVC) standard aims at much higher coding efficiency, but the cost is the greatly increased computation complexity. Among all the coding modules, DCT and IDCT are frequently called and bring a lot of complexity burden. While, the Single Instruction Multiple data (SIMD) technique has been widely used to speed up media data process. In this paper, we focus on SIMD acceleration of HEVC DCT and IDCT, and the implementation is conducted on 64-bit multicore platform. For DCT optimization, intermediate variables are processed in less bit width and parallel processing level is significantly improved with little compression efficiency loss. Experiment results on 64-bit Tilera multicore platform exhibit that the proposed SIMD implementation can greatly reduce about 40%–70% computational complexity of DCT and IDCT with negligible compression performance loss. © 2015 Taylor & Francis Group.

关键词： Video signal processing

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Improving image compression Performance by Spatial-Channel Context Adaptive Model 4

Improving Image Compression Performance by Spatial-Channel C...

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4th International conference on Electronic Communication and Artificial Intelligence, ICECAI 2023

作者： Wang, Hao Wang, Huifen Xue, Junda Lu, Enmin Wang, Hanming Wu, Zijun Song, Yunlong Institute of Big Data and Artificial Intelligence China Telecom Corporation Limited Beijing Research Institute Beijing China

ISBN: (纸本)9798350314496

the significance of enhancing image compression efficiency for machine vision, analysis, and comprehension tasks has gained increasing recognition. In response to this need, we propose and implement a novel method called ELIC (Efficient Learned image compression with Unevenly Grouped Space-Channel Contextual Adaptive coding) to achieve high compression efficiency. Our method is evaluated on the classic Openimage V6 Common Test Condition (CTC) eval datasets, and its performance is compared to baseline methods for machine vision tasks. the results of our study demonstrate a substantial enhancement in compression efficiency, suggesting that the ELIC technique holds promise for pushing the boundaries of state-of-the-art visual compression for vision tasks. Furthermore, we believe that our approach can promote the application of learning-based image compression. © 2023 IEEE.

关键词： image compression

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New Method for Adaptive Lossless compression of Still images Based on the Histogram Statistics

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4th International conference on Intelligent Interactive Multimedia Systems and Services (IIMSS)

作者： Kountchev, Roumen Todorov, Vladimir Kountcheva, Roumiana Tech Univ Sofia Dept Radio Commun & Video Technol Sofia 1000 Bulgaria T&K Engn Co Sofia 1712 Bulgaria

ISBN: (纸本)9783642221583

the method for adaptive lossless image coding is aimed at efficient compression of grayscale or color digital still images. the method is based on the analysis of the processed images histograms, followed by modified Huffman and Run-length coding. the coding is performed in two consecutive stages. In the first one, the input data (i. e., the digital information about the image brightness and color components) is transformed without affecting their volume in such a way, that to obtain sequences of same values (in particular, zeros) of maximum length. the transform is reversible and is based on the analysis of the input data histograms and on the differences between each number in the processed data and the most frequent one. In the second stage of the processing the transformed data is analyzed and sequences of same numbers are detected. Every such sequence is substituted by a shorter one, corresponding to the number of same values which it contains. the method is extremely suitable for images of graphics or texts (for example: fingerprints, contour images, cartoons, medical signals, etc.). the method has low computational complexity and is suitable for real-time applications.

关键词： Lossless image compression adaptive run-length coding histogram-adaptive lossless image compression

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Object/image relations and vision metrics I

Object/image relations and vision metrics I

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conference on mathematics of data/image coding, compression, and encryption VI, with Applications

作者： Stiller, PF Texas A&M Univ Inst Sci Computat College Stn TX 77843 USA

ISBN: (纸本)0819450812

In this paper and its sequel, we will examine two fundamental problems related to object recognition for the generalized weak perspective model of image formation. We offer a complete solution to both problems for configurations of point features. Geometric Constraints (Object/image Equations): the problem of single view recognition is central to many image understanding and computer vision tasks. the results in this paper provide a way to understand the relationship that exists between the 3D geometry and its "residual" in a 2D image. this relationship is completely characterized (for a particular combination of features) by a set of fundamental equations in the 3D and 2D shape coordinates. these equations are know as object/image relations. they can be used to test for the geometric consistency between an object and an image. For example, by fixing point features on a known object, we get constraints on the 2D shape coordinates of possible images of those features. Conversely, if we have specific 2D features in an image, we will get constraints on the 3D shape coordinates of objects capable of producing that image. this yields a test for which object is being viewed. the object/image equations are thus fundamental tools for the identification/recognition problem. In this paper we give the complete solution, and find explicitly, the object/image equations for point features in the generalized weak perspective case. this entails working on spaces known as Grasssmannians and exploiting certain incidence correspondences and the so-called Phicker relations. Vision Metrics: We would like to know if two configurations of a fixed number of points in 2D or 3D are the same if we allow affine transformations. If they are, then we want a distance of zero, and if not, we want a distance that expresses their dissimilarity - always recounizing that we can transform the points. the Procrustes metric, described in the shape theory literature [4], provides such a notion of distance

关键词： invariants Grassmann manifolds affine transformations object recognition image understanding object/image relations metrics Plucker coordinates

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A Feature Oriented Framework and Enhanced Assessments for Imaging compression∗ 4

A Feature Oriented Framework and Enhanced Assessments for Im...

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4th IEEE International conference on image Processing, Applications and Systems, IPAS 2020

作者： Redford, Jesse Li, Xingjie University of North Carolina Charlotte Department of Mechanical Engineering CharlotteNC United States University of North Carolina Charlotte Department of Mathematics and Statistics CharlotteNC United States

ISBN: (纸本)9781728175744

this paper offers a new feature-oriented compression algorithm for flexible reduction of data redundancy commonly found in images and videos streams. Using a combination of image segmentation and face detection techniques as a preprocessing step, we derive a compression framework to adaptively treat 'feature' and 'ground' while balancing the total compression and quality of 'feature' regions. We demonstrate the utility of a feature compliant compression algorithm (FC-SVD), a revised peak signal-To-noise ratio PSNR assessment, and a relative quality ratio to control artificial distortion. the goal of this investigation is to provide new contributions to image and video processing research via multi-scale resolution and the block-based adaptive singular value decomposition. © 2020 IEEE.

关键词： image compression

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