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Joint classification of multiresolution representations with discrimination analysis for SAR ATR

JOURNAL OF ELECTRONIC IMAGING 2018年第4期27卷 043030-043030页

作者： Zhang, Zhenyu Zhejiang Univ Sci & Technol Sch Automat & Elect Engn Hangzhou Zhejiang Peoples R China

This paper proposes an automatic target recognition of synthetic aperture radar image by joint classification of multiresolution representations with discrimination analysis. The multiresolution representations are generated to better convey the inner discriminability of the original image. Considering the extended operating conditions (EOCs) in practical applications, it is preferred that those resolutions, which make little contributions to correct target recognition, are not used. Accordingly, the discrimination analysis is performed to select the resolutions with notably high discriminability for the present operating conditions based on their reliability levels calculated from sparse representation-based classification. Afterward, the selected resolutions are jointly classified based on joint sparse representation for target recognition. Finally, extensive experiments are conducted on the moving and stationary target acquisition and recognition dataset under both the standard operating condition and various EOCs. The results validate the effectiveness and robustness of the proposed method. (C) 2018 SPIE and IS&T

关键词： synthetic aperture radar automatic target recognition multiresolution representations discrimination analysis joint sparse representation

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Real-Time Visualization of Large-Scale Geological Models With Nonlinear Feature-Preserving Levels of Detail

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IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 2023年第2期29卷 1491-1505页

作者： Sicat, Ronell Ibrahim, Mohamed Ageeli, Amani Mannuss, Florian Rautek, Peter Hadwiger, Markus King Abdullah Univ Sci & Technol Thuwal 23955 Saudi Arabia Saudi Aramco Dhahran 31311 Saudi Arabia

The rapidly growing size and complexity of 3D geological models has increased the need for level-of-detail techniques and compact encodings to facilitate interactive visualization. For large-scale hexahedral meshes, state-of-the-art approaches often employ wavelet schemes for level of detail as well as for data compression. Here, wavelet transforms serve two purposes: (1) they achieve substantial compression for data reduction;and (2) the multiresolution encoding provides levels of detail for visualization. However, in coarser detail levels, important geometric features, such as geological faults, often get too smoothed out or lost, due to linear translation-invariant filtering. The same is true for attribute features, such as discontinuities in porosity or permeability. We present a novel, integrated approach addressing both purposes above, while preserving critical data features of both model geometry and its attributes. Our first major contribution is that we completely decouple the computation of levels of detail from data compression, and perform nonlinear filtering in a high-dimensional data space jointly representing the geological model geometry with its attributes. Computing detail levels in this space enables us to jointly preserve features in both geometry and attributes. While designed in a general way, our framework specifically employs joint bilateral filters, computed efficiently on a high-dimensional permutohedral grid. For data compression, after the computation of all detail levels, each level is separately encoded with a standard wavelet transform. Our second major contribution is a compact GPU data structure for the encoded mesh and attributes that enables direct real-time GPU visualization without prior decoding.

关键词： Geological models structured hexahedral meshes multiresolution representations interactive visualization

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A Volumetric Approach to Point Cloud Compression-Part I: Attribute Compression

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IEEE TRANSACTIONS ON IMAGE PROCESSING 2020年 29卷 2203-2216页

作者： Chou, Philip A. Koroteev, Maxim Krivokuca, Maja Google Inc Seattle WA 98103 USA Imatrex Inc Moscow 121205 Russia INRIA Ctr Rech Rennes Bretagne Atlantique F-35042 Rennes France

Compression of point clouds has so far been confined to coding the positions of a discrete set of points in space and the attributes of those discrete points. We introduce an alternative approach based on volumetric functions that are functions defined not just on a finite set of points but throughout space. As in regression analysis, volumetric functions are continuous functions that are able to interpolate values on a finite set of points as linear combinations of continuous basis functions. Using a B-spline wavelet basis, we are able to code volumetric functions representing both geometry and attributes. Geometry compression is addressed in Part II of this paper, while attribute compression is addressed in Part I. Attributes are represented by a volumetric function whose coefficients can be regarded as a critically sampled orthonormal transform that generalizes the recent successful Region-Adaptive Hierarchical (or Haar) Transform to higher orders. Experimental results show that attribute compression using higher order volumetric functions is an improvement over the first-order functions used in the emerging MPEG point cloud compression standard.

关键词： Three-dimensional displays Image coding Geometry Transforms Octrees Splines (mathematics) Hilbert space Bezier volumes B-splines wavelets point cloud compression color coding attribute coding multiresolution representations graph signal processing counting measure

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A Volumetric Approach to Point Cloud Compression-Part II: Geometry Compression

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IEEE TRANSACTIONS ON IMAGE PROCESSING 2020年 29卷 2217-2229页

作者： Krivokuca, Maja Chou, Philip A. Koroteev, Maxim 8i Wellington New Zealand INRIA Ctr Rech Rennes Bretagne Atlantique F-35042 Rennes France 8i Seattle WA USA Google Inc Seattle WA 98103 USA Imatrex Inc Moscow 141400 Russia

Compression of point clouds has so far been confined to coding the positions of a discrete set of points in space and the attributes of those discrete points. We introduce an alternative approach based on volumetric functions, which are functions defined not just on a finite set of points, but throughout space. As in regression analysis, volumetric functions are continuous functions that are able to interpolate values on a finite set of points as linear combinations of continuous basis functions. Using a B-spline wavelet basis, we are able to code volumetric functions representing both geometry and attributes. Attribute compression is addressed in Part I of this paper, while geometry compression is addressed in Part II. Geometry is represented implicitly as the level set of a volumetric function (the signed distance function or similar). Experimental results show that geometry compression using volumetric functions improves over the methods used in the emerging MPEG Point Cloud Compression (G-PCC) standard.

关键词： Bezier volumes B-splines wavelets point cloud compression geometry coding shape coding multiresolution representations signed distance function graph signal processing

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Feature Enhancement of Noisy Image by Dyadic Wavelet Analysis

Feature Enhancement of Noisy Image by Dyadic Wavelet Analysi...

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2017 2nd International Conference on Computer, Mechatronics and Electronic Engineering(CMEE 2017)

作者： Zheng-hong HUANG Li XIA Chongqing Engineering Laboratory for Detection Control and Integrated System School of Computer Science and Technology Chongqing Technology and Business University School of mathematics and statistics Chongqing Technology and Business University

The image de-noising method is proposed by multiresolution representations of the dyadic wavelet transformation. Firstly, the original image are decomposed using dyadic wavelet transformation, then the image can be de-noised by way of adopting different thresholds according to the different scales of wavelet coefficients, and finally nonlinear enhancing function are applied for wavelet coefficients with the enhancement method in the corresponding scales. Experiments of the medical images show that compared to the image enhancement method, our approach improves the information entropy and contrast improvement index of the images, enhances edge texture of images.

关键词： Dyadic wavelet transform multiresolution representations Threshold function Image enhancement

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CPH: A Compact Representation for Hierarchical Meshes Generated by Primal Refinement

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COMPUTER GRAPHICS FORUM 2015年第8期34卷 155-166页

作者： Untereiner, L. Kraemer, P. Cazier, D. Bechmann, D. Inria F-54600 Villers Les Nancy France Univ Strasbourg ICube CNRS Strasbourg France

We present CPH (Compact Primal Hierarchy): a compact representation of the hierarchical connectivity of surface and volume manifold meshes generated through primal subdivision refinements. CPH is consistently defined in several dimensions and supports multiple kinds of tessellations and refinements, whether regular or adaptive. The basic idea is to store only the finest mesh, encoded in a classical monoresolution structure that is enriched with a minimal set of labels. These labels allow traversal of any intermediate level of the mesh concurrently without having to extract it in an additional structure. Our structure allows attributes to be stored on the cells not only on the finest level, but also on any intermediate level. We study the trade-off between the memory cost of this compact representation and the time complexity of mesh traversals at any resolution level.

关键词： multiresolution representations data structures subdivision levels of detail adaptive subdivision

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n-Dimensional multiresolution representation of subdivision meshes with arbitrary topology

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GRAPHICAL MODELS 2013年第5期75卷 231-246页

作者： Untereiner, Lionel Cazier, David Bechmann, Dominique Univ Strasbourg CNRS UMR 7357 IGG TeamICube F-67412 Illkirch Graffenstaden France

We present a new model for the representation of n-dimensional multiresolution meshes. It provides a robust topological representation of arbitrary meshes that are combined in closely interlinked levels of resolution. The proposed combinatorial model is formalized through the mathematical model of combinatorial maps allowing us to give a general formulation, in any dimensions, of the topological subdivision process that is a key issue to robustly and soundly define mesh hierarchies. It fully supports multiresolution edition what allows the implementation of most mesh processing algorithms - like filtering or compression - for n-dimensional meshes with arbitrary topologies. We illustrate this model, in dimension 3, with an new truly multiresolution representation of subdivision volumes. It allows us to extend classical subdivision schemes to arbitrary polyhedrons and to handle adaptive subdivision with an elegant solution to compliance issues. We propose an implementation of this model as an effective and relatively inexpensive data structure. (C) 2013 Elsevier Inc. All rights reserved.

关键词： multiresolution representations Data structures Subdivision volumes Levels of detail Boundary representation Adaptive subdivision

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A multiresolution model for small-body gravity estimation

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CELESTIAL MECHANICS & DYNAMICAL ASTRONOMY 2011年第3期111卷 309-335页

作者： Jones, Brandon A. Beylkin, Gregory Born, George H. Provence, Robert S. Univ Colorado Colorado Ctr Astrodynam Res Boulder CO 80309 USA Univ Colorado Dept Appl Math Boulder CO 80309 USA NASA Aerosci & Flight Mech Div Johnson Space Ctr Houston TX 77058 USA

A new model, dubbed the MRQSphere, provides a multiresolution representation of the gravity field designed for its estimation. The multiresolution representation uses an approximation via Gaussians of the solution of the Laplace's equation in the exterior of a sphere. Also, instead of the spherical harmonics, variations in the angular variables are modeled by a set of functions constructed using quadratures for the sphere invariant under the icosahedral group. When combined, these tools specify the spatial resolution of the gravity field as a function of altitude and required accuracy. We define this model, and apply it to representing and estimating the gravity field of the asteroid 433 Eros. We verified that a MRQSphere model derived directly from the true spherical harmonics gravity model satisfies the user defined precision. We also use the MRQSphere model to estimate the gravity field of Eros for a simulated satellite mission, yielding a solution with accuracy only limited by measurement errors and their spatial distribution.

关键词： Gravity modeling Spherical harmonics Gravity estimation Quadratures for the sphere multiresolution representations Asteroid Eros

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Random distributed multiresolution representations with significance querying

Random distributed multiresolution representations with sign...

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5th International Conference on Informational Processing in Sensor Networks

作者： Wang, Wei Ramchandran, Kannan Univ Calif Berkeley Dept Elect Engn & Comp Sci Berkeley CA 94720 USA

ISBN: (纸本)1595933344

We propose random distributed multiresolution representations of sensor network data, so that the most significant encoding coefficients are easily accessible by querying a few sensors, anywhere in the network. Less significant encoding coefficients are available by querying a larger number of sensors, local to the region of interest. Significance can be defined in a multiresolution way, without any prior knowledge of the source data, as global summaries versus local details. Alternatively, significance can be defined in a data-adaptive way, as large differences between neighboring data values. We propose a distributed encoding algorithm that is robust to arbitrary wireless communication connectivity graphs, where links can fail or change with time. This randomized algorithm allows distributed computation that does not require strict global coordination or awareness of network connectivity at individual sensors. Because computations involve sensors in local neighborhoods of the communication graph, they are communication-efficient. Our framework uses local interaction among sensors to enable flexible information retrieval at the global level.

关键词： multiresolution representations arbitrary communication graphs robust distributed algorithms wireless sensor networks

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Filtering and rendering of resolution-dependent reflectance models

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IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 2008年第2期14卷 412-425页

作者： Tan, Ping Lin, Stephen Quan, Long Guo, Baining Shum, Heung-Yeung HKUST Dept Comp Sci & Engn Kowloon Hong Kong Peoples R China Beijing Sigma Ctr Beijing 100080 Peoples R China

The reflectance of a surface depends upon the resolution at which it is imaged. In this work, we propose to represent this resolution-dependent reflectance as a mixture of multiple conventional reflectance models and present a framework for efficiently rendering the reflectance effects of such mixture models over different resolutions. To rapidly determine reflectance at runtime with respect to resolution, we record the mixture model parameters at multiple resolution levels in mipmaps and propose a technique to minimize aliasing in the filtering of these mipmaps. This framework can be applied to several widely used parametric reflectance models and can be implemented in graphics hardware for real-time processing, using a presented hardware-accelerated technique for nonlinear filtering of mixture model parameters. In addition, shadowing and masking effects can be included into this framework to increase the realism of rendering. With this mixture model filtering and rendering framework, our system can efficiently render the fine reflectance detail that is customarily disregarded in conventional rendering methods.

关键词： reflectance and shading models multiresolution representations scale-dependent reflectance mipmap filtering

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