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Auto Center Find Density Peaks Algorithm and its Application in Face image Clustering

Auto Center Find Density Peaks Algorithm and its Application...

引用

signal, Information and Data processing (ICSIDP), IEEE International conference on

作者： GuiYan Wang ChangJiang Bu YueSheng Luo Harbin Finance University Harbin China College of Automation Harbin Engineering University Harbin China

ISBN: (数字)9781728123455

ISBN: (纸本)9781728123462

Face image clustering is one of the most important applications in digital signal process. Here, Find Density Peaks clustering algorithm with auto choosing centers is proposed and applied into the face image clustering problem. In the clustering process, the Complex wavelet structural Similarity Index is introduced to quantize the difference between two face images. The deciding mechanism of two key parameters are modified. Avoiding the false centers, the true centers of each cluster are auto defined. And the face images dataset are properly clustered. The face images are dimensionality reduced and visualized via T-SNE as scatter points in 2D space. The results show a good partition of face images dataset. And the proposed algorithm shows practical values in most applications required with clustering.

关键词： Clustering FDP CW-SSIM T-SNE face images

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Bi-orthogonal filter banks with directional vanishing moments [image representation applications]

Bi-orthogonal filter banks with directional vanishing moment...

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

作者： A.L. da Cunha M.N. Do Department of Electrical and Computer Engineering Coordinated Science Laboratory University of Illinois Urbana-Champaign Urbana-Champaign IL USA

In this paper we study 2D nonseparable filter banks that annihilate information along a certain discrete direction. This is done by having filters with directional vanishing moments (DVM). We study the approximation property of such filters and the design problem providing conditions for its solvability. In particular, we completely characterize the solution and propose a design procedure utilizing the mapping technique. Nonlinear approximation experiments with the contourlet transform indicate that compared with the traditional filters, the new filters designed with DVM provide gains in SNR and visual quality due to their short size.

关键词： Channel bank filters Filter bank wavelet transforms image representation image recognition Geometry Tree data structures Frequency Information filtering Information filters

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Lossy compression of hyperspectral images by using Enhanced Multivariance Products Representation (EMPR) method

Lossy compression of hyperspectral images by using Enhanced ...

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IEEE signal processing and Communications applications (SIU)

作者： Aleksei Sukhanov Süha Tuna Behçet Uğur Töreyin ArtGe Teknoloji mühendislik san. tic. ltd. şti. İstanbul Türkiye Istanbul Teknik Universitesi Istanbul TR

In preceding paper, a compression algorithm for hyperspectral images using a novel multivariate data decomposition method called Enhanced Multivariance Products Representation (EMPR) is developed. The test results obtained by performing some EMPR approximations of different orders and their qualities are reported. In order to improve performance, EMPR approach is applied to high-subband of hyperspectral data which is spectrally decorrelated using Haar wavelet transform. Low subbands are losslessly compressed using JPEG2000 Proposed methods are tested with AVIRIS data, promising compression vs. Peak-signal-to-Noise Ratios (PSNR) are obtained.

关键词： Transform coding Hyperspectral imaging image coding wavelet transforms Decorrelation

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A scalable video compression algorithm for real-time Internet applications

A scalable video compression algorithm for real-time Interne...

引用

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

作者： M. Johanson Alkit Communications AB Molndal Sweden

Ubiquitous use of real-time video communication on the Internet requires adaptive applications that can provide different levels of quality depending on the amount of resources available. For video coding this means that the algorithms must be designed to be scalable in terms of bandwidth, processing requirements and quality of the reconstructed signal. This paper presents a novel video compression and coding algorithm targeted at delay-sensitive applications in heterogeneous network and computing environments. The algorithm, based on the embedded zerotree wavelet algorithm for still image compression, generates a highly scalable layered bitstream that can be decoded at different qualities in terms of spatial resolution, frame rate and compression distortion. Furthermore, the algorithm is designed to require only a minimal coding delay, making it suitable for highly interactive applications like videoconferencing. The performance of the proposed algorithm is evaluated by comparison with a nonscalable codec and the penalty in compression efficiency that the scalability requirement imposes is analyzed. The codec is shown to produce a scalable bitstream ranging from about 10 kbps to 10 Mbps, while the computational complexity is kept at a level that makes software implementation on CPU-constrained equipment feasible.

关键词： Video compression Internet image coding Algorithm design and analysis Codecs Video coding signal design Bandwidth image reconstruction signal processing

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An Efficient and Highly Parallel Hyperspectral imagery Compression Scheme Based on Distributed Source Coding

An Efficient and Highly Parallel Hyperspectral Imagery Compr...

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Asilomar conference on signals, Systems & Computers

作者： Ngai-Man Cheung Antonio Ortega Signal and Image Processing Institute Ming Hsieh Department of Electrical Engineering University of Southern California Los Angeles CA USA

This paper extends our previous work on hyperspectral imagery compression based on distributed source coding (DSC). We apply DSC principles to facilitate efficient parallel encoder implementations with moderate memory requirement. Based on our previously proposed wavelet-based DSC framework, we propose a novel adaptive coding scheme that judiciously combines DSC and intra coding tools, taking into account the source statistics and inter-band correlation, as well as the coding gains and limitations imposed by tools. Bits extracted from wavelet coefficients tend to have different statistics and inter-band correlation at different significance levels and in different wavelet subbands. Therefore, it is non-trivial to determine the optimal coding strategy. Toward this we propose modeling techniques to estimate the performance of DSC/intra coding under different bits extraction scenarios. This model is used to define adaptive coding strategies that can optimally incorporate different bit- extraction techniques with DSC/intra coding tools according to the bit significance levels and wavelet subbands. Experimental results demonstrate that adaptive coding can achieve up to 4dB improvement over a non-adaptive system, and the improved DSC-based system is comparable to some 3D wavelet system in terms of coding performance. While we focus on hyperspectral images in this paper, many of the proposed techniques are applicable to other wavelet- based DSC image and video applications.

关键词： Hyperspectral imaging image coding Source coding Adaptive coding wavelet coefficients Statistics Decoding Filtering Memory management signal processing

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A 3D discrete curvelet based method for segmenting dynamic textures

A 3D discrete curvelet based method for segmenting dynamic t...

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IEEE International conference on image processing

作者： Sloven Dubois Renaud Péteri Michel Ménard MIA - Laboratoire Mathématiques Image et Applications Avenue Michel Crépeau 17042 La Rochelle France Image et Applications MIA-Laboratoire Mathématiques La Rochelle France L3i-Laboratoire Informatique Image et Interaction La Rochelle France

This paper presents a new approach for segmenting a video sequence containing dynamic textures. The proposed method is based on a 2D+T curvelet transform and an octree hierarchical representation. The curvelet transform enables to outline spatio-temporal structures of a given scale and orientation. The octree structure based on motion coherence enables a better spatio-temporal segmentation than a direct application of the 2D+T curvelet transform. Our segmentation method is successfully applied on video sequences of dynamic textures. Future prospects are finally exposed.

关键词： Discrete transforms Video sequences Frequency domain analysis image segmentation Discrete wavelet transforms Layout signal processing image sequences Surface texture

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An Attention Based wavelet Convolutional Model for Visual Saliency Detection

An Attention Based Wavelet Convolutional Model for Visual Sa...

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IEEE International conference on Acoustics, Speech and signal processing

作者： Reshmi S. Bhooshan Suresh K College of Engineering Trivandrum Thiruvananthapuram India Govt. Engineering College Thiruvananthapuram India

ISBN: (纸本)9781728176055;9781728176062

The emergence of deep neural architectures greatly enhanced the accuracy of salient region detection algorithms that plays a vital role in computer vision applications. However, the accurate extraction of regions with fine boundaries still remains as a challenge. In this work, an attention based wavelet Convolutional Neural Network (WCNN) is implemented that efficiently extracts the spatial, spectral and semantic features of the image in multiple resolution and it turns out to be suitable for locating the visually salient regions. Further enhancement of the fine boundaries of the predicted map is made possible by the inclusion of a combinational loss function of balanced cross entropy loss, SSIM loss and edge loss. The effectiveness of the method is evaluated using three benchmark datasets and the results shows better performance achieving a minimum Mean Absolute Error (MAE) of 0.032 and maximum F-measure of 0.938.

关键词： Visualization Convolution image edge detection Semantics Benchmark testing Feature extraction Entropy

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A Comparison of x-lets in Denoising cDNA Microarray images

A Comparison of x-lets in Denoising cDNA Microarray Images

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IEEE International conference on Acoustics, Speech and signal processing

作者： Rouzbeh Shams Hossein Rabbani Saeed Gazor Electrical & Computer Engineering Department Isfahan University of Technology Isfahan Iran Biomedical Engineering Department Medical Image & Signal Processing Research Center Isfahan University of Medical Science Isfahan 81745319 Iran Electrical & Computer Engineering Department Queen's University Kingston Canada

ISBN: (纸本)9781479928941

Microarray technology has become a power tool in the field of bioinformatics. It is used to measure gene expression levels and similar to any other image capturing processes is prone to noise. There are different kinds of noise, during preparation, hybridization and scanning in microarray images which usually are modeled by Gaussian noise. Since introduction of wavelets in 1970s, many more forms and extensions of this transform have been developed and used, such as stationary wavelet transform (SWT), complex wavelet transform (CWT), curvelet transform (CURV) and contourlet transform (CNT). By developing of more sparse transforms, it is important to have a perspective of how efficient the transforms are in different applications, such as microarray image analysis. In this paper, we compare the efficiency of common sparse transforms including ordinary discrete wavelet transform (DWT), SWT, CWT, CURV, CNT, Contourlet-SD decomposition, steerable pyramid (STP) and shearlet transform (SHR) for microarray image denoising. Therefore after converting microarray image into x-let transform, BayesShrink method, soft and hard thresholding are used to perform denoising of these images. Both local and general thresholds are calculated for each subband in order to evaluate the effect of incorporating intrascale dependency on top of sparsity property in statistical modeling of x-let's coefficients. Our simulation results show that CWT and SHR outperforms the others when using global thresholding and SWT is the preferred transform when using local thresholding. Although STP and SHR have better performance for some criteria like structural similarity (SSIM) index, but CWT is faster.

关键词： microarray denoising x-let transform wavelet Noise reduction Transform Microarray wavelets Standard Widget Toolkit Electric tools images SHIELDED PAIR global thresholding Local threshold

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An efficient, high speed architecture for JPEG2000 MQ-coder

An efficient, high speed architecture for JPEG2000 MQ-coder

引用

International image processing, applications and Systems conference (IPAS)

作者： Layla Horrigue Taoufik Saidani Refka Ghodhbani Mohamed Atri Faculty of Sciences Electronics and Micro-Electronics Laboratory Monastir Tunisia

JPEG is the most commonly used image compression standard in today's world. Researchers have found that JPEG has many limitations, in order to overcome all those limitations and to add on new improved features, ISO and ITU-T have come up with new image compression standard, which is JPEG2000. The JPEG2000 is intended to provide a new image coding/decoding system using state of the art compression techniques, based on the use of two important parts coding/decoding processes which are wavelet Transform and Arithmetic Coding. As it's hard to meet the real-time requirement of image compression systems by software, it is necessary to implement compression system by hardware. The embedded block coding with optimized truncation (EBCOT) algorithm is the heart of the JPEG 2000 image compression system. Context Based Adaptive Arithmetic coding is used and the MQ coder is adopted in the JPEG2000. In this paper we propose efficient faster architecture for the JPEG2000 MQ-Coder which is implemented in VHDL hardware description language and synthesized using Xilinx's design flows ISE 13.1. The implementation results show that the design operates at 354.937 MHz when implemented on Virtex-6. Post synthesis simulations indicate that the proposed architecture is able to compress 35 video frames/s of high definition TV of 1920p.

关键词： Transform coding Field programmable gate arrays Registers Random access memory Propagation losses Discrete wavelet transforms Quantization (signal)

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Edge Detection of Noise images Based on Improved Canny Algorithm with Adaptive Threshold

Edge Detection of Noise Images Based on Improved Canny Algor...

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Advances in Electrical Engineering and Computer applications( AEECA), 2020 IEEE International conference on

作者： Jing Zhang School of Modern Health and Regimen Industry Anhui Sanlian University Hefei China

ISBN: (纸本)9798350355260

Edge detection is a significant research direction in the fields of image processing and computer vision, widely applied in image segmentation, object detection, and other areas. The traditional Canny edge detection algorithm excels in noise resistance and edge localization, but it still faces challenges such as edge information loss and the need for manual setting of dual thresholds when processing noisy images. This paper proposes an improved Canny edge detection algorithm with adaptive thresholds, which effectively addresses the deficiencies of the traditional Canny algorithm in noise suppression and threshold setting by introducing a wavelet filter and an adaptive threshold determination method based on Otsu's method for maximizing the between-class variance. Experimental results on the BSD500 dataset demonstrate that the proposed algorithm performs excellently in edge detection of noisy images, with an accuracy improvement of approximately 5%-10% compared to the traditional Canny algorithm.

关键词： Location awareness image segmentation Accuracy image edge detection Noise reduction Manuals Approximation algorithms Discrete wavelet transforms Noise measurement signal to noise ratio

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