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

共 249 条记录，以下是221-230 订阅

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ConvAE-512: Bandwidth-Efficient image compression in Edge with Auto-Encoders

ConvAE-512: Bandwidth-Efficient Image Compression in Edge wi...

引用

Innovation in Technology (ASIANCON), Asian conference on

作者： Aditya Kotha Sainath Reddy Sankepally Murukuri S V S V Vasanth Nishoak Kosaraju Mayank Lovanshi Rajesh Ingle Computer Science and Engineering IIIT Naya Raipur Data Science and Artificial Intelligence IIIT Naya Raipur

ISBN: (数字)9798350354218

ISBN: (纸本)9798350354225

the exponential growth in data creation and transmission, particularly high-resolution images, poses a significant challenge to network bandwidth, necessitating advanced compression techniques. this paper introduces ConvAE-512, a novel convolutional neural network-based encoder-decoder architecture optimized for edge computing environments. Our approach significantly outperforms existing lossy compression algorithms in image fidelity while efficiently reducing data transmission size and network utilization. ConvAE-512 achieves a compression rate of 6x, outperforming traditional Direct compression with a higher Structural Similarity Index (SSIM) of 0.9150 and a Peak Signal-to-Noise Ratio (PSNR) of 27.15 dB, underscoring its efficiency in preserving image quality despite compression. these results establish ConvAE-512 as an advanced alternative for efficient image compression, adeptly balancing quality retention and compression ratio.

关键词： image quality Technological innovation image coding PSNR image edge detection Propagation losses Indexes data communication Convolutional neural networks Edge computing

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Signals and image Processing in Information Systems by Tensor Analysis Methods

Signals and Image Processing in Information Systems by Tenso...

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IEEE International conference on Advanced Trends in Information theory (ATIT)

作者： Dmytro Kucherov Valerii Tkachenko Natalia Khalimon Olexii Poshyvailo National Aviation University Kyiv Ukraine

ISBN: (纸本)9798350332636

the paper deals with the problem of signal and image processing by means of tensor analysis. Within the framework of the considered approach, a short review of existing methods is given, which includes general approaches such as the principal component analysis, independent component analysis, canonical correlation analysis, and particular practical problems, which include blind signal separation and image compression. All these methods are united by the need to perform a singular value decomposition operation, for which the input data must be structured by a matrix or their sequence. Reducing the size of the core matrix representation by discarding non-essential components allows you to present data in a compact form. Joint diagonalization of a sequence of matrices produces satisfactory results assuming that the data or signal sets are statistically independent. the presented data are considered in two examples, allowing us to clearly assess the advantage of the presented approach.

关键词： Tensors image coding Market research Matrix decomposition Object recognition Singular value decomposition Periodic structures

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Based on Embedded Zerotree Wavelet coding data compression Algorithm Research of NC Machine Tool Control System

Based on Embedded Zerotree Wavelet Coding Data Compression A...

引用

International conference on Mechanical, Control and Computer Engineering (ICMCCE)

作者： Xiaoxue Li Peng Zhang Enming Hui Ge Chen School of Mechanical and Traffic Engineering Ordos Institute of Technology Ordos China College of Mechanical Engineering Inner Mongolia University of Science and Technology Baotou China National NC System Engineering Research Center Huazhong University of Science Wuhan China

ISBN: (数字)9781728146898

ISBN: (纸本)9781728146904

the core of intelligent manufacturing is Cyber-Physical system. In order to establish high frequency sampling of Cyber-Physical system, massive data is needed. It is necessary to study the efficient transmission technology of real-time data. data compression is through the omitted part is not necessary or redundant, transfer and storage in finite strip width, and storage space for more information of a technical means. Embedded Wavelet coding (Embedded Zero tree Wavelet, EZW) is based on Wavelet transform multi-resolution analysis technology, extract the Embedded Zero tree, and variable length of quantization and coding compression, transmission and decompression algorithm. this paper mainly studies the numerical control machine tool electric control instruction domain representative of the current loop of data in the data for one dimensional data was designed based on the EZW algorithm binary tree structure of zero tree and Huffman encoding to achieve further compression. Verification experiment and application results showed that, the algorithm on the basis of the guarantee accuracy has good compression ratio and efficiency.

关键词： Encoding Wavelet coefficients Discrete cosine transforms image coding Computer numerical control Big data

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A secure image steganography technique with moderately higher significant bit embedding

A secure image steganography technique with moderately highe...

引用

International conference on Computer Communication and Informatics (ICCCI)

作者： Piyush Kumar Gupta Ratnakirti Roy Suvamoy Changder Department of Computer Applications National Institute of Technology Durgapur India

Steganography is a process to hide secret data into a cover media in an imperceptible manner. In the spatial domain of image steganography, the most common technique is Least Significant Bit Replacement (LSBR). However, LSBR is extremely sensitive to compression attacks involving truncation of LSBs. As a possible solution to the drawback of the traditional LSBR scheme, this paper proposes an image steganography technique that embeds secret data in the moderately higher significant bits such as 4 th or 5 th bit of a pixel. the proposed method uses a color image as a cover and according to pixel values; three groups of pixels are maintained. these groups are used for selecting the candidate pixels for 4th or 5th bit embedding. It also implements an optimal pixel adjustment process (OPAP) to minimize the visual distortion due to embedding. In addition to the OPAP, a method for randomly dispersing the secret data bits is also implemented making it harder for an adversary to detect hidden information. the experimental results for proposed method showed high values for Peak Signal to Noise Ratio (PSNR) signifying High stego-image fidelity.

关键词： Visualization PSNR Media image coding Payloads Computers Informatics

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Adaptive data mapping of wavelet compressed images in MIMO systems

Adaptive data mapping of wavelet compressed images in MIMO s...

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IEEE Region 8 International Symposium on Video/image Processing and Multimedia Communications (EURASIP)

作者： S. Plevel T. Javornik G. Kandus R. Trobec Jožef Stefan Institute Ljubljana Slovenia

the adaptive data mapping of wavelet compressed images in multiple input multiple output (MIMO) wireless communication systems is proposed and analyzed. image compression methods based on wavelet transform allow image decomposition in blocks, representing signal frequency bands at different resolutions. Blocks representing low frequencies are very important for visual image quality, while the highest frequency blocks, even lost, have almost no impact on image quality. MIMO systems offer parallel subchannels with different quality. Mapping more important data to higher quality subchannels improves the image quality. the results obtained by analog devices wavelet algorithm, implemented in a single chip ADV601, used in the MIMO system with four transmit and four receive antennas, show that the adaptive data mapping approach improves the peak signal to noise ratio (PSNR) up to 8 dB in comparison to standard data mapping.

关键词： image coding MIMO Frequency image quality Signal mapping PSNR Adaptive systems Wavelet analysis Wireless communication image analysis

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Technology of coding Video images in Structure-Cluster Space to Increase Efficiency and Reliability

Technology of Coding Video Images in Structure-Cluster Space...

引用

IEEE International conference on Advanced Trends in Information theory (ATIT)

作者： Vladimir Barannik Andrii Krasnorutsky Vitalii Kolesnyk Roman Onyshchenko V. N. Karazin Kharkiv National University Kharkiv Ukraine Ivan Kozhedub Kharkiv National Air Force University Kharkiv Ukraine State Research Institute of Armament and Military Equipment Testing and Certification Chernihiv Ukraine Kharkov National University of Radio Electronics Kharkiv Ukraine

ISBN: (纸本)9798350332636

the imbalance between the reliability of the received information and the speed of its reception, taking into account onboard channels of transmission of video data is justified. the information concerning reducing the informational intensity of video data existing technologies’ shortcomings is given. Among such shortcomings: the gain of efficiency is compensated by the semantic component of the video destruction. therefore, the risk of informational reliability losing increases. Among such shortcomings: the gain of efficiency is compensated by the semantic component of the video destruction. therefore, the risk of informational reliability losing increases. Among such shortcomings: the gain of efficiency is compensated by the semantic component of the video destruction. therefore, the risk of informational reliability losing increases. It is proposed to solve the imbalance by developing new methods of encoding transformed video images. this will increase the level of transformed video compression in ensuring the desired reliability conditions. the information about the transformed video segments encoding in case of their preliminary clustering usage is provided. It is justified that clustering of video segments takes into account the number of series in the binary syntax description of the transformer components. the main stages of the developed forming structural clusters of clustered component-transforms, according to the meaning of their double description – number of unit’s series method are given..

关键词： Resistance image segmentation image coding Semantics Redundancy Video compression Syntactics

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compression of Bayer Colour Filter Array images

Compression of Bayer Colour Filter Array Images

引用

IEEE International conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT)

作者： Shridhar Patil P Deepika R. V. College of Engineering Bengaluru India

ISBN: (数字)9781728106304

ISBN: (纸本)9781728106311

Bayer Colour Filter Array is a matrix of photosensors covered with red, green, and blue colour filters. this setup is advantageous in smartphones as only a third of the required data is captured by the sensor in the camera. the rest of the components based on the colour format can be interpolated using a suitable algorithm to arrive at a full-colour image. Increasing the resolution of the camera sensor will translate to increased bandwidth in the image signal processing pipeline, and consequently power consumption. In addition to that, the bit depth is also on the rise to enhance the colours. these two factors will create a huge impact on the data to be handled in the pertinent processor. Hence, compression of the Bayer data is of immense significance. the existing standard compression schemes can be adapted to suit the Bayer format. Also, several compression schemes, specific to Bayer format have been proposed. Two compression methods, viz. JPEG-LS and Hierarchical Prediction based compression have been tested and the corresponding results are presented in this paper. the former is a standard while the latter has been proposed keeping the Bayer format in mind. Modelling of the algorithms shows that JPEG-LS is best suited in the use cases where lossless compression is desirable, and Hierarchical Prediction based compression is the better option where some amount of loss is acceptable.

关键词： image coding image color analysis Interpolation Standards Context modeling Prediction algorithms Transforms

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An Optimization Scheme of Cloud Desktop Video Transmission Based on X2Go KDrive Protocol

An Optimization Scheme of Cloud Desktop Video Transmission B...

引用

Electronic Information Engineering and Computer Communication (EIECC), International conference on

作者： Shuang Liang Danqi Ma School of Computer and Artificial Intelligence Southwest Jiaotong University Chengdu

ISBN: (数字)9798331534622

ISBN: (纸本)9798331534639

Cloud desktop has the advantages of security, easy management, low comprehensive cost, and can meet the needs of mobile office. Cloud desktop based on B/S architecture also has a lot of performance optimization space, in the low-bandwidth network video playback will be stuck, bandwidth usage is too high, response time is too long and other problems. therefore, this paper proposes a cloud desktop video transmission optimization scheme based on X2Go KDrive protocol, and designs an image block caching algorithm and a hybrid coding algorithm based on video detection. First, the client and the server maintain synchronous image block cache, and then the server detects the video area of the cloud desktop, and adopts H.264 video coding for the image block of the video area and JPEG image coding for the common area. Finally, the mark value of the unchanged image block in the block cache and the compressed data of the changed image block are assembled together to form the final transmission data and sent to the client. After receiving such data, the client can distinguish the unchanged image block and the changed image block, process them respectively, and restore the original image to the screen. the experimental results show that this optimization scheme effectively reduces the network bandwidth occupation during video playback, improves the fluency of video playback, and optimizes the performance of cloud desktop video transmission.

关键词： Video coding Protocols image coding Transform coding Bandwidth Streaming media Video compression Servers Time factors Optimization

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iCostale: Adaptive Cost Optimization for Storage Clouds

iCostale: Adaptive Cost Optimization for Storage Clouds

引用

IEEE International conference on Cloud Computing, CLOUD

作者： Sandip Agarwala Divyesh Jadav Luis A. Bathen IBM Almaden Research Center San Jose CA USA University of California Irvine CA USA

the unprecedented volume of data generated by contemporary business users and consumers has created enormous data storage and management challenges. In order to control data storage cost, many users are moving their data to online storage clouds, and applying capacity usage reducing data transformation techniques like de-duplication, compression, and transcoding. these give rise to several challenges, such as which cloud to choose, and what data transformation techniques to apply for optimizing cost. this paper presents an integrated storage service called 'iCostale' that reduces the overall cost of data storage through automatic selection and placement of users' data into one of many storage clouds. Further, it intelligently transforms data based on its type, access frequency, transformation overhead, and the cost model of the storage cloud providers. We demonstrate the efficacy of iCostale through a series of micro- and application-level benchmarks. Our experimental results show that, through intelligent data placement and transformation, 'iCostale' can reduce overall cost of data storage by more than 50%.

关键词： Pricing Cloud computing data models image coding Computational modeling Memory Optimization

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Potential of SIFT, SURF, KAZE, AKAZE, ORB, BRISK, AGAST, and 7 More Algorithms for Matching Extremely Variant image Pairs

Potential of SIFT, SURF, KAZE, AKAZE, ORB, BRISK, AGAST, and...

引用

International conference on Computing, mathematics and Engineering Technologies (iCoMET)

作者： Shaharyar Ahmed Khan Tareen Rana Hammad Raza Pakistan Navy Engineering College (PNEC) National University of Sciences and Technology (NUST) Karachi Pakistan

Extremely variant image pairs include distorted, deteriorated, and corrupted scenes that have experienced severe geometric, photometric, or non-geometric-non-photometric transformations with respect to their originals. Real world visual data can become extremely dusty, smoky, dark, noisy, motion-blurred, affine, JPEG compressed, occluded, shadowed, virtually invisible, etc. therefore, matching of extremely variant scenes is an important problem and computer vision solutions must have the capability to yield robust results no matter how complex the visual input is. Similarly, there is a need to evaluate feature detectors for such complex conditions. With standard settings, feature detection, description, and matching algorithms typically fail to produce significant number of correct matches in these types of images. though, if full potential of the algorithms is applied by using extremely low thresholds, very encouraging results are obtained. In this paper, potential of 14 feature detectors: SIFT, SURF, KAZE, AKAZE, ORB, BRISK, AGAST, FAST, MSER, MSD, GFTT, Harris Corner Detector based GFTT, Harris Laplace Detector, and CenSurE has been evaluated for matching 10 extremely variant image pairs. MSD detected more than 1 million keypoints in one of the images and SIFT exhibited a repeatability score of 99.76% for the extremely noisy image pair but failed to yield high quantity of correct matches. Rich information is presented in terms of feature quantity, total feature matches, correct matches, and repeatability scores. Moreover, computational costs of 25 diverse feature detectors are reported towards the end, which can be used as a benchmark for comparison studies.

关键词： Visualization image coding Feature detection Transform coding Detectors Feature extraction Computational efficiency

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