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Three-dimensional steerable discrete cosine transform with application to 3d image compression

MULTIdIMENSIONAL SYSTEMS ANd SIGNAL PROCESSING 2021年第2期32卷 491-519页

作者： Lima, Verusca S. Madeiro, Francisco Lima, Juliano B. Univ Fed Pernambuco Dept Elect & Syst Recife PE Brazil Univ Pernambuco Polytech Sch Pernambuco Recife PE Brazil

This work introduces the three-dimensional steerable discrete cosine transform (3d-SdCT), which is obtained from the relationship between the discrete cosine transform (dCT) and the graph Fourier transform of a signal on a path graph. One employs the fact that the basis vectors of the 3d-dCT constitute a possible eigenbasis for the Laplacian of the product of such graphs. The proposed transform employs a rotated version of the 3d-dCT basis. We then evaluate the applicability of the 3d-SdCT in the field of 3d medical image compression. We consider the case where we have only one pair of rotation angles per block, rotating all the 3d-dCT basis vectors by the same pair. The obtained results show that the 3d-SdCT can be efficiently used in the referred application scenario and it outperforms the classical 3d-dCT.

关键词： Signal processing on graphs Graph Fourier transform discrete cosine transform 3d image compression

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Volume rendering oriented 3d image compression using wavelet transform

Volume rendering oriented 3D image compression using wavelet...

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3rd International Conference on Signal Processing (ICSP 96)

作者： Zhang, JC Yang, BZ Institute of Information Science Northern Jiaotong University Beijing China

ISBN: (纸本)7505338900

In this paper we propose a 3d image compression method which is volume rendering oriented and uses wavelet transform. Via separable wavelet transform, dataset is decomposed into subbands with different importance to rendering process. According to this difference, an efficient classified quantization and a bit allocation strategy are designed,and zero-tree structure is used to represent zero coefficients.

关键词： data compression image coding rendering (computer graphics) transform coding wavelet transforms tree data structures quantisation (signal) volume rendering 3d image compression wavelet transform efficient classified quantization bit allocation strategy zero-tree structure zero coefficients

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image sequence compression using adapted three-dimensional transform: Application to scintigraphic images

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SIGNAL PROCESSING-image COMMUNICATION 1999年第3期15卷 255-263页

作者： Ploix, A Vigouroux, B IUT Troyes LAM Equipe Image LTI F-10026 Troyes France LINA IUT Angers F-49016 Angers France

compression results obtained by using the three-dimensional discrete cosine transform are presented. The key aspects of the paper concern the adaptation to the 3d case of transform coding algorithms that are most often used in the 2d case. This work focussed on two particular aspects that are the original contribution of this paper: (i) the adaptation to the 3d case of transform coefficients quantization method;(ii) the application of an octree analysis algorithm before transform. The algorithm was especially designed for tomographic images issued from scintigraphic measures, we finally obtained a compression rate of 100 for a quality measured by a 40 dB PSNR. (C) 1999 Elsevier Science B.V. All rights reserved.

关键词： 3d image compression adaptive 3d cosine transform octree analysis tomographic images scintigraphy

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Tensor block-wise singular value decomposition for 3d point cloud compression

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MULTIMEdIA TOOLS ANd APPLICATIONS 2022年第26期81卷 37917-37938页

作者： Tamilmathi, A. Christoper Chithra, P. L. Univ Madras Dept Comp Sci Guindy Campus Chennai 600025 Tamil Nadu India

A novel and efficient block-wise decomposition-based codec (BdC) for a three-dimensional (3d) light detection and ranging (LidAR) point cloud (PCd) image (BdCPCd) has been introduced in this paper. The raw LidAR data is cleansed and normalized by applying the axis outlier detection and circular differential cosine transformation methods, respectively. Then, the iterative dimensionality reduction approach is used to decompose and quantize the tensor structured signal data through block-wise singular value decomposition and signal block vectorization methods, respectively. The final single order tensor is considered as a compressed bitstream for efficient transformation. The proposed BdCPCd is applied on three different dense 3d LidAR PCd data sets. The results demonstrate that it outperformed the four existing well-known compression techniques, such as WinRAR, 7-Zip, Tensor Tucker decomposition, and Random sample consensus (RANSAC) point cloud compression algorithm. This iterative compression algorithm constantly reduces the 66.66% of tensor blocks in each iteration. This research proves that the BdCPCd compresses different sizes of 3d LidAR PCd spatial data to be reduced into six bytes and averagely increases the quality of the decompressed image by 1.6 decibels than the existing Tucker based algorithm.

关键词： 3d point cloud LidAR 3d image compression Singular value decomposition Tensor decomposition Spatial information

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Integral image compression methods

Integral image compression methods

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Conference on Optical Information Systems IV

作者： Stern, Adrian Javidi, Bahram Ben Gurion Univ Negev Dept Electroopt Engn IL-84105 Beer Sheva Israel

ISBN: (纸本)0819463906

Integral imaging (II) is a promising technique for sensing and visualizing of three dimensional (3d) images because it produces autostereoscopic images without special illumination requirements. As with any 3d imaging, in order to produce high quality 3d images, it is required to capture, record, transmit, process and display an enormous amount of optical data. Therefore, a central challenge that rises is to store and transmit efficiently the huge amount of information. This can be done by applying appropriate data compression techniques that remove efficiently the inherent redundancy within the captured data. In this work we survey previously developed II compression methods and, compare their performance. We present a new technique to cope with a common problem with some of the II compression methods, namely the choice of the compression depth to be applied in the various dimensions representing an II.

关键词： integral imaging 3d image compression MPEG-2 JPEG JPEG2000 ray phase space

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Real-time compression architecture for efficient coding in autostereoscopic displays

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JOURNAL OF REAL-TIME image PROCESSING 2010年第1期5卷 45-56页

作者： Chaikalis, d. P. Sgouros, N. P. Maroulis, d. E. Sangriotis, M. S. Univ Athens Dept Informat & Telecommun Athens 15784 Greece

Integral imaging is a promising technique for delivering high-quality three-dimensional content. However, the large amounts of data produced during acquisition prohibits direct transmission of Integral image data. A number of highly efficient compression architectures are proposed today that outperform standard two-dimensional encoding schemes. However, critical issues regarding real-time compression for quality demanding applications are a primary concern to currently existing Integral image encoders. In this work we propose a real-time FPGA-based encoder for Integral image and integral video content transmission. The proposed encoder is based on a highly efficient compression algorithm used in Integral Imaging applications. Real-time performance is achieved by realizing a pipelined architecture, taking into account the specific structure of an Integral image. The required memory access operations are minimized by adopting a systolic concept of data flow through the core processing elements, further increasing the performance boost. The encoder targets, real-time, broadcast-type high-resolution Integral image and video sequences and performs three orders of magnitude faster than the analogous software approach.

关键词： Integral imaging disparity estimation 3d image compression FPGA Real-time processing

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Lossy to lossless compressions of hyperspectral images using three-dimensional set partitioning algorithm

Lossy to lossless compressions of hyperspectral images using...

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Conference on Electronic Imaging and Multimedia Technology IV

作者： Wu, JJ Wu, ZS Wu, CK Xidian Univ Sch Sci Xian 710071 Peoples R China

ISBN: (纸本)081945592X

In this paper, we present a three-dimensional (3d) hyperspectral image compression algorithm based on zeroblock coding and wavelet transforms. An efficient Asymmetric 3d wavelet Transform (AT) based on the lifting technique and packet transform is used to reduce redundancies in both the spectral and spatial dimensions. The implementation via 3d integer lifting scheme allows to map integer-to-integer values, enabling lossy and lossless decompression from the same bit stream. To encode these coefficients after Asymmetric 3d wavelet transform, a modified 3dSPECK algorithm - Asymmetric Transform 3d Set Partitioning Embedded bloCK (AT-3dSPECK) is proposed. According to the distribution of energy of the transformed coefficients, the 3dSPECK's 3d set partitioning block algorithm and the 3d octave band partitioning scheme are efficiently combined in the proposed AT-3dSPECK algorithm. Several AVIRIS images are used to evaluate the compression performance. Compared with the JPEG2000, AT-3dSPIHT and 3dSPECK lossless compression techniques, the AT-3dSPECK achieves the best lossless performance. In lossy mode, the AT-3dSPECK algorithm outperforms AT-3dSPIHT and 3dSPECK at all rates. Besides the high compression performance, AT-3dSPECK supports progressive transmission. Clearly, the proposed AT-3dSPECK algorithm is a better candidate than several conventional methods.

关键词： hyperspectral images 3d image compression wavelet transform 3dSPECK zeroblock coding

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