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检索条件"任意字段=Conference on Wavelet Applications in Signal and Image Processing VIII"

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Mathematical analysis of the energy compaction affected by the dimensionality of Karhunen-Lòeve transform

Mathematical analysis of the energy compaction affected by t...

引用

IEEE International conference on image processing

作者： Yukihiro Bandoh Hiroki Ohbayashi Seishi Takamura Kazuto Kamikura Yoshiyuki Yashima NTT Cyber Space Laboratories NTT Company Limited Yokosuka Kanagawa Japan Faculty of Sciences Kyushu University Fukuoka Japan

ISBN: (纸本)9781424456536;9781424456543

Transform coding is a essential tool for picture coding applications, and coding schemes that can achieve high energy compaction are essential. In terms of energy compaction, Karhunen-Loeve transform (KLT) is known to be optimal. The energy compaction provided by KLT depends on the statistical property of the input signal and the dimensionality of KLT. However, the quantitative effect of KLT dimensionality on energy compaction has not been clarified. This paper establishes a mathematical model of the relationship among the dimensionality of KLT and the energy compaction of the transform coefficients, using mathematical tools in quantum information theory.

关键词： Mathematical analysis Compaction Karhunen-Loeve transforms Discrete cosine transforms Mathematical model Discrete transforms Transform coding Discrete wavelet transforms Quantum mechanics Information theory

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wavelet coding of polygonal mesh data based on triangular lattice structure with expanded nodes

Wavelet coding of polygonal mesh data based on triangular la...

引用

IEEE International conference on image processing

作者： M. Tsunoda T. Terasaki K. Fukuda A. Kawanaka Department of Electrical and Electronics Engineering Faculty of Science and Technology Sophia University Japan

Efficient representations of a 3D object shape and its textural data have attracted wide attention for the transmission of computer graphics data and for interactive design in manufacturing. Polygonal mesh data, which consist of connectivity information, geometric data and textural data are often used for representing a 3D object in many applications. We propose a compression method for polygonal mesh data by structuring its geometric and textural data on a triangular lattice with expanded nodes. The structuralized geometric and textural data are compressed using a 2D signal coding method. Experimental results following from the application of the new method to polygonal mesh data show that the proposed scheme performs efficiently.

关键词： Lattices Shape Computer graphics Surface texture Geometry Tree graphs Data engineering Design engineering Computer aided manufacturing Application software

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Zero Reference based Low-light Enhancement with wavelet Optimization

Zero Reference based Low-light Enhancement with Wavelet Opti...

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IEEE conference on Advanced Video and signal Based Surveillance (AVSS)

作者： Vivek Deshmukh Adinath Dukre Ashutosh Kulkarni Prashant W. Patil Santosh Kumar Vipparthi Subrahmanyam Murala Anil Balaji Gonde Shri Guru Gobind Singhji Institute of Engineering and Technology Nanded India CVPR Lab Indian Institute of Technology Ropar India Indian Institute of Technology Guwahati India CVPR Lab School of Computer Science and Statistics Trinity College Dublin Ireland

ISBN: (数字)9798350374285

ISBN: (纸本)9798350374292

images captured in low light conditions usually suffer from poor visibility, a high amount of noise, and little information stored in the dark image, which has a negative impact on subsequent processing for outdoor computer vision applications. Presently, numerous deep learning based methods achieved superior performance with multi-exposure paired training data or additional information. However, obtaining multi-exposure data samples is a tedious task in real-time scenarios. To mitigate this challenge, we propose a zero reference based learnable wavelet approach without multi-exposure paired training data requirement for low-light image enhancement. Our proposed approach generates the low light image and learns to project an image into noise free similar looking image, then we enhance the image using retinex theory. Further, we have proposed learnable wavelet block to remove the hidden noise amplified while enhancement. We introduce Gaussian-based supervision to improve the smoothness of the image. Extensive experimental analysis on synthetic as well as real-world images, along with thorough ablation study demonstrate the effectiveness of our proposed method over the existing state-of-the-art methods for low-light image enhancement. The code is provided at https://***/vision-lab-sggsiet/Zero-Reference-based-Low-light-Enhancement-with-wavelet-Optimization.

关键词： Training Reflectivity Deep learning Computer vision Surveillance Noise Training data

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Optimal JPEG2000 encoder mechanism for low delay and efficient distribution of HDTV programs

Optimal JPEG2000 encoder mechanism for low delay and efficie...

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International conference on Acoustics, Speech, and signal processing (ICASSP)

作者： S. Naito A. Koike S. Matsumoto KDDI Research and Development Laboratories Inc. Kamifukuoka Saitama Japan

Motion JPEG2000 has been developed as a new video coding standard for motion pictures, utilizing the still image coding standard JPEG2000. Motion JPEG2000 specifies a normative bitstream syntax that the decoder must recognize and allows flexible selection of detailed coding parameters at the encoder. The compression performance largely depends, therefore, on the encoder design. However, the simple implementation of JPEG2000 encoder might cause picture quality degradation due specifically to wavelet image coding of interlaced TV signals and unsatisfactory bit assignments. That degradation might then become conspicuous in subjective picture quality especially during low bit-rate coding. To overcome this problem, we investigated an optimal design for a Motion JPEG2000 encoder that can be used for primary distribution applications of HDTV programs, assuming that the available bit-rate is approximately 50 Mbps. Our study introduces advanced key technologies not yet recognized officially. Coding experiments using those technologies confirmed that a significant coding gain was achieved versus conventional encoding schemes.

关键词： Delay HDTV Transform coding image coding Standards development Degradation Video coding Motion pictures Decoding TV

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Improvements to SPIHT for Lossless image Coding

Improvements to SPIHT for Lossless Image Coding

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International conference on Information and Communication Technologies: From Theory to applications, ICTTA

作者： T. Brahimi A. Melit F. Khelifi D. Boutana Department of Electronic Engineering Faculty of Engineering Science University of Jijel Algeria Queen''s University Belfast UK

The SPIHT (set partitioning in hierarchical trees) algorithm has attracted great attention in recent years as a technique for image coding. Not only does it give good objective and subjective performance, it is also simple and efficient. In this paper we propose an enhanced image lossless image compression that is based on SPIHT. The most important modification in this algorithm is the addition of a simple modification to the set of type A with a new test on the threshold. Our experiments show that this improvement increases the performance of lossless image coding for all standard test images

关键词： image coding wavelet transforms Testing image resolution Decoding Partitioning algorithms Performance loss signal processing algorithms Scalability Video compression

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Block motion estimation using wavelet filtering

Block motion estimation using wavelet filtering

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International conference on Acoustics, Speech, and signal processing (ICASSP)

作者： H.F. Ates M.T. Orchard Electrical Engineering Department Princeton University Princeton NY USA

Block matching motion compensation achieves savings in residual error energy at the cost of motion vector bit rate. While this tradeoff has proven valuable for many video sequences, there are many obvious examples of blocks for which the cost of motion vectors is not offset by the gains of motion compensation. This paper proposes a multiresolution framework for motion compensated prediction that offers a richer set of options for trading off motion compensation accuracy against the cost of motion vectors. The method improves the prediction at motion boundaries and on covered/uncovered regions, while reducing the bit rate by using less accurate motion vectors in smoother regions. The new algorithm is compared to the full-search block matching in various simulations, and the results show that the algorithm achieves a 10 to 30% reduction in motion vector bit rate. These saving are particularly important in low bit rate applications where motion overhead constitutes a significant percentage of overall bit rate.

关键词： Motion estimation Bit rate Costs Frequency Entropy Motion compensation Predictive models Filtering image sequences image coding

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Face recognition using Homomorphic Filtering as a pre-processing technique

Face recognition using Homomorphic Filtering as a pre-proces...

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International conference on Emerging Trends in Communication, Control, signal processing & Computing applications (C2SPCA)

作者： Nihal Winston D'Cunha Sachin A Birajdhar K Manikantan S Ramachandran Dept. of Electronics and Communication Engg. M.S. Ramaiah Inst. of Tech. Bangalore INDIA Dept. of Electronics and Communication Engg. S.J.B. Inst. of Tech. Bangalore INDIA

The appearance of the face will vary drastically when illumination, pose and expression change. Variations in these conditions make Face Recognition (FR) an even more challenging and difficult task. In this paper, we propose three novel techniques, viz., Homomorphic Filtering (HF), image Flip (IF) and Raster Scan Mapping (RSM), to improve the performance of a FR system. HF is a pre-processing technique used to normalize the illumination variations. IF is used to neutralize pose and expression variations. RSM is used to map 2D to 1D, to increase the ability to store the intensity value of all the spotted lines. DWT and DCT are used for efficient feature extraction and a Binary Particle Swarm Optimization based feature selection algorithm is used to search the feature space for the optimal feature subset. Experimental results show the promising performance of the proposed techniques for FR on four benchmark face databases, namely, CMUPIE, Color FERET, UMIST and ORL databases.

关键词： Databases Lighting Feature extraction Discrete wavelet transforms Hafnium Discrete cosine transforms Vectors

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Design and implementation of a novel architecture for symmetric FIR filters with boundary handling on Xilinx Virtex FPGAs

Design and implementation of a novel architecture for symmet...

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IEEE International conference on Field-Programmable Technology (FPT)

作者： A. Benkrid K. Benkrid D. Crookes School of Computer Science Queen''s University Belfast Belfast UK

Symmetric FIR filters, which provide linear phases, are frequently used in digital signal processing. This paper presents the design and implementation of a novel architecture for symmetric FIR filters on Xilinx Virtex FPGAs. The architecture is particularly useful for handling the problem of processing signal boundaries, which occurs in finite length signal processing (e.g. image processing). Based on bit parallel arithmetic, our architecture is fully scalable and parameterised. It takes into account the details of the symmetry and exploits the features of Xilinx Virtex FPGAs. The implementation leads to considerable area savings compared to conventional implementations (based on a hard router), at the expense of using a clock doubler, which reduces the overall processing speed. The latter is however still high enough to achieve real time performance. Moreover, our architecture can match the speed of a conventional implementation if the filter output is going to be decimated, as it is the case in multirate applications (e.g. wavelets).

关键词： Finite impulse response filter Field programmable gate arrays Nonlinear filters signal processing Clocks Convolution Computer architecture Discrete wavelet transforms Reflection Hardware

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Shearlet transform based image denoising using histogram thresholding

Shearlet transform based image denoising using histogram thr...

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International conference on Communication Systems and Networks (ComNet)

作者： T S Anju N R Nelwin Raj Department of ECE Sree Chitra Thirunal College of Engineering Trivandrum Kerala

ISBN: (纸本)9781509033508

This paper presents an efficient image denoising method by incorporating shearlet-based histogram thresholding. Nowadays, digital images are used in wide range of applications but most of these images are degraded during transmission and acquisition process. Removal of noise from images is still a challenging task for many researchers because there is always a trade-off between noise removal and fine edge preservation. This paper is based on image denoising using shearlet transform. Shearlets have excellent features for data analysis and processing, which overcomes the limitation of traditional methods. They are optimally sparse and have multi-scale and multi-directional properties which are optimal in representing image containing edges. In this paper, the proposed method is found to produce superior peak signal-to-noise ratio (PSNR) over the conventional denoising algorithms.

关键词： Histograms image denoising Noise reduction Algorithm design and analysis image edge detection wavelet transforms

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Optimizing Compressed Sensing with Taylor Sunflower Algorithm: A Performance Analysis of Hybrid Techniques for Biomedical Imaging and Video Surveillance

Optimizing Compressed Sensing with Taylor Sunflower Algorith...

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Innovations in High Speed Communication and signal processing (IHCSP), International conference on

作者： Asha Rajiv Santosh Kumar S. Arul Antran Vijay Prabhat Sharma Ranjusha J P Prateek Aggarwal School of Sciences Physics & Electronics JAIN (Deemed to be University) Bangalore Karnataka India AIDS Vishwakarma Institute of Technology Pune India Department of Computer Science Engineering Karpagam College of Engineering Coimbatore India Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India Department of S&H Prince Shri Venkateshwara Padmavathy Engineering College Chennai India Chitkara Centre for Research and Development Chitkara University Himachal Pradesh India

ISBN: (数字)9798350368949

ISBN: (纸本)9798350368956

A powerful area that seeks to minimize the amount of space of signals that are compressible or sparse in a specific base representation that uses compressed recognizing in video streaming applications. A sparse signal provides a good approximation of the signal since the representation is sparse and the amplitude of the coefficient’s decays according to the power law. The process of projecting signals into a space with low dimensions results in measurement vectors. A sparse signal may be accurately reconstructed using the measurement vector. Imprecise or noisy data that may nevertheless be compressed and used for approximation purposes. images in the frequency or wavelet domain are suitable for Compressed Sensing because they are inherently compressible. Reconstructed images are of higher quality, and the compression ratio—the ratio of an image's pixel count to its measurement vector—has been reduced, enabling more precise reconstruction. Taylor SFO based CS is a two-stage optimization technique for picture compression and recovery that aims to enhance the quality of models with high correlation and low redundancy. An image that uses self-replication and 3D change to compress itself is first processed in the early phase. In the last step, the CS uses SSIM to recover pictures using an ensemble sparseness estimate and Taylor SFO parameters.

关键词： image coding wavelet domain Three-dimensional displays Frequency-domain analysis Biomedical measurement Streaming media Extraterrestrial measurements Vectors Noise measurement image reconstruction

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