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Journal articles on the topic 'Lossless reconstruction'

Author: Grafiati

Published: 4 June 2021

Last updated: 15 February 2022

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1

Bassiouni, Mostafa A. "High-fidelity integrated lossless/lossy compression and reconstruction of images." Optical Engineering 32, no. 8 (1993): 1848. http://dx.doi.org/10.1117/12.145390.

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Wang Hongjuan, 王红娟, 王志鹏 Wang Zhipeng, 海涛 Hai Tao, 刘旭焱 Liu Xuyan, and 秦怡 Qin Yi. "Lossless Binary Image Reconstruction in Diffractive Encryption System with Redundant Data." Chinese Journal of Lasers 42, no. 7 (2015): 0709002. http://dx.doi.org/10.3788/cjl201542.0709002.

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Devaki, P. "Lossless Reconstruction of Secret Image Using Threshold Secret Sharing and Transformation." International Journal of Network Security & Its Applications 4, no. 3 (2012): 111–19. http://dx.doi.org/10.5121/ijnsa.2012.4307.

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Priya, C., T. Kesavamurthy, and M. Uma Priya. "An Efficient Lossless Medical Image Compression Using Hybrid Algorithm." Advanced Materials Research 984-985 (July 2014): 1276–81. http://dx.doi.org/10.4028/www.scientific.net/amr.984-985.1276.

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Recently many new algorithms for image compression based on wavelets have been developed.This paper gives a detailed explanation of SPIHT algorithm with the combination of Lempel Ziv Welch compression technique for image compression by MATLAB implementation. Set partitioning in Hierarchical trees (SPIHT) is one of the most efficient algorithm known today. Pyramid structures have been created by the SPIHT algorithm based on a wavelet decomposition of an image. Lempel Ziv Welch is a universal lossless data compression algorithm guarantees that the original information can be exactly reproduced f

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Aaker, Ole Edvard, Espen Birger Raknes, Ørjan Pedersen, and Børge Arntsen. "Wavefield reconstruction for velocity–stress elastodynamic full-waveform inversion." Geophysical Journal International 222, no. 1 (2020): 595–609. http://dx.doi.org/10.1093/gji/ggaa147.

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SUMMARY Gradient computations in full-waveform inversion (FWI) require calculating zero-lag cross-correlations of two wavefields propagating in opposite temporal directions. Lossless media permit accurate and efficient reconstruction of the incident field from recordings along a closed boundary, such that both wavefields propagate backwards in time. Reconstruction avoids storing wavefield states of the incident field to secondary storage, which is not feasible for many realistic inversion problems. We give particular attention to velocity–stress modelling schemes and propose a novel modificati

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Hejrati, Behzad, Abdolhossein Fathi, and Fardin Abdali-Mohammadi. "A new near-lossless EEG compression method using ANN-based reconstruction technique." Computers in Biology and Medicine 87 (August 2017): 87–94. http://dx.doi.org/10.1016/j.compbiomed.2017.05.024.

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Setyaningsih, Emy, and Agus Harjoko. "Survey of Hybrid Image Compression Techniques." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 4 (2017): 2206. http://dx.doi.org/10.11591/ijece.v7i4.pp2206-2214.

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A compression process is to reduce or compress the size of data while maintaining the quality of information contained therein. This paper presents a survey of research papers discussing improvement of various hybrid compression techniques during the last decade. A hybrid compression technique is a technique combining excellent properties of each group of methods as is performed in JPEG compression method. This technique combines lossy and lossless compression method to obtain a high-quality compression ratio while maintaining the quality of the reconstructed image. Lossy compression technique

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Hennenfent, Gilles, Lloyd Fenelon, and Felix J. Herrmann. "Nonequispaced curvelet transform for seismic data reconstruction: A sparsity-promoting approach." GEOPHYSICS 75, no. 6 (2010): WB203—WB210. http://dx.doi.org/10.1190/1.3494032.

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We extend our earlier work on the nonequispaced fast discrete curvelet transform (NFDCT) and introduce a second generation of the transform. This new generation differs from the previous one by the approach taken to compute accurate curvelet coefficients from irregularly sampled data. The first generation relies on accurate Fourier coefficients obtained by an [Formula: see text]-regularized inversion of the nonequispaced fast Fourier transform (FFT) whereas the second is based on a direct [Formula: see text]-regularized inversion of the operator that links curvelet coefficients to irregular da

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Schlaeger, S. "A fast TDR-inversion technique for the reconstruction of spatial soil moisture content." Hydrology and Earth System Sciences 9, no. 5 (2005): 481–92. http://dx.doi.org/10.5194/hess-9-481-2005.

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Abstract. Spatial moisture distribution in natural soil or other material is a valuably information for many applications. Standard measurement techniques give only mean or punctual results. Therefore a new inversion algorithm has been developed to derive moisture profiles along single TDR sensor-probes. The algorithm uses the full information content of TDR reflection data measured from one or both sides of an embedded probe. The system consisting of sensor probe and surrounded soil can be interpreted as a nonuniform transmission-line. The algorithm is based on the telegraph equations for non

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Schlaeger, S. "A fast TDR-inversion technique for the reconstruction of spatial soil moisture content." Hydrology and Earth System Sciences Discussions 2, no. 3 (2005): 971–1009. http://dx.doi.org/10.5194/hessd-2-971-2005.

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Abstract. Spatial moisture distribution in natural soil or other material is a valuably information for many applications. Standard measurement techniques give only mean or pointwise results. Therefore a new inversion algorithm has been developed to derive moisture profiles along single TDR sensor-probes. The algorithm uses the full information content of TDR reflection data measured from one or both sides of an embedded probe. The system consisting of sensor probe and surrounded soil can be interpreted as a nonuniform transmission-line. The algorithm is based on the telegraph equations for no

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11

Prasetyo, Heri, Chih-Hsien Hsia, and Alim Wicaksono Hari Prayuda. "Progressive Secret Sharing with Adaptive Priority and Perfect Reconstruction." Journal of Imaging 7, no. 4 (2021): 70. http://dx.doi.org/10.3390/jimaging7040070.

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A new technique for progressive visual secret sharing (PVSS) with adaptive priority weight is proposed in this paper. This approach employs the bitwise and eXclusive-OR (XOR) based approaches for generating a set of shared images from a single secret image. It effectively overcomes the former scheme limitation on dealing with an odd number of stacked or collected shared images in the recovery process. The presented technique works well when the number of stacked shared images is odd or even. As documented in experimental results, the proposed method offers good results over binary, grayscale,

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Wang, Yongjie, Jia Chen, Qinghong Gong, Xuehu Yan, and Yuyuan Sun. "Weighted Polynomial-Based Secret Image Sharing Scheme with Lossless Recovery." Security and Communication Networks 2021 (May 25, 2021): 1–11. http://dx.doi.org/10.1155/2021/5597592.

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In some particular scenes, the shadows need to be given different weights to represent the participants’ status or importance. And during the reconstruction, participants with different weights obtain various quality reconstructed images. However, the existing schemes based on visual secret sharing (VSS) and the Chinese remainder theorem (CRT) have some disadvantages. In this paper, we propose a weighted polynomial-based SIS scheme in the field of GF (257). We use k , k threshold polynomial-based secret image sharing (SIS) to generate k shares and assign them corresponding weights. Then, the r

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Vaidyanathan, P. P., T. Q. Nguyen, Z. Doganata, and T. Saramaki. "Improved technique for design of perfect reconstruction FIR QMF banks with lossless polyphase matrices." IEEE Transactions on Acoustics, Speech, and Signal Processing 37, no. 7 (1989): 1042–56. http://dx.doi.org/10.1109/29.32282.

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Zhang, Jiani, Jennifer Erway, Xiaofei Hu, Qiang Zhang, and Robert Plemmons. "Randomized SVD Methods in Hyperspectral Imaging." Journal of Electrical and Computer Engineering 2012 (2012): 1–15. http://dx.doi.org/10.1155/2012/409357.

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We present a randomized singular value decomposition (rSVD) method for the purposes of lossless compression, reconstruction, classification, and target detection with hyperspectral (HSI) data. Recent work in low-rank matrix approximations obtained from random projections suggests that these approximations are well suited for randomized dimensionality reduction. Approximation errors for the rSVD are evaluated on HSI, and comparisons are made to deterministic techniques and as well as to other randomized low-rank matrix approximation methods involving compressive principal component analysis. Nu

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d’Andrea, Valeria, and Manlio De Domenico. "Compressing Phase Space Detects State Changes in Nonlinear Dynamical Systems." Complexity 2020 (July 22, 2020): 1–6. http://dx.doi.org/10.1155/2020/8650742.

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Equations governing the nonlinear dynamics of complex systems are usually unknown, and indirect methods are used to reconstruct their manifolds. In turn, they depend on embedding parameters requiring other methods and long temporal sequences to be accurate. In this paper, we show that an optimal reconstruction can be achieved by lossless compression of system’s time course, providing a self-consistent analysis of its dynamics and a measure of its complexity, even for short sequences. Our measure of complexity detects system’s state changes such as weak synchronization phenomena, characterizing

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Doganata, Z., P. P. Vaidyanathan, and T. Q. Nguyen. "General synthesis procedures for FIR lossless transfer matrices, for perfect-reconstruction multirate filter bank applications." IEEE Transactions on Acoustics, Speech, and Signal Processing 36, no. 10 (1988): 1561–74. http://dx.doi.org/10.1109/29.7544.

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Tsai, Chang-Lung, Huei-Fen Chiang, Kuo-Chin Fan, and Char-Dir Chung. "Reversible data hiding and lossless reconstruction of binary images using pair-wise logical computation mechanism." Pattern Recognition 38, no. 11 (2005): 1993–2006. http://dx.doi.org/10.1016/j.patcog.2005.03.001.

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Basha, Shaik Mahaboob, and B. C. Jinaga. "A Novel Optimized Golomb-Rice Technique for the Reconstruction in Lossless Compression of Digital Images." ISRN Signal Processing 2013 (August 7, 2013): 1–5. http://dx.doi.org/10.1155/2013/539759.

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The research trends that are available in the area of image compression for various imaging applications are not adequate for some of the applications. These applications require good visual quality in processing. In general the tradeoff between compression efficiency and picture quality is the most important parameter to validate the work. The existing algorithms for still image compression were developed by considering the compression efficiency parameter by giving least importance to the visual quality in processing. Hence, we proposed a novel lossless image compression algorithm based on G

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Chuanchao, Zhang. "Two-level fusion big data compression and reconstruction framework combining second-generation wavelet and lossless compression." Complex & Intelligent Systems 6, no. 3 (2020): 607–20. http://dx.doi.org/10.1007/s40747-020-00158-z.

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Wu, Hangbin, Zeran Xu, Chun Liu, et al. "LV-GCNN: A lossless voxelization integrated graph convolutional neural network for surface reconstruction from point clouds." International Journal of Applied Earth Observation and Geoinformation 103 (December 2021): 102504. http://dx.doi.org/10.1016/j.jag.2021.102504.

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Mostarac, Petar, Roman Malarić, Katarina Mostarac, and Marko Jurčević. "Noise Reduction of Power Quality Measurements with Time-Frequency Depth Analysis." Energies 12, no. 6 (2019): 1052. http://dx.doi.org/10.3390/en12061052.

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This paper presents the noise reduction of power quality measurement with time-frequency (T-F) depth analysis. Noise reduction is achieved with wavelet transformation by decomposition, thresholding and lossless reconstruction of signal. Three main problems with T-F noise reduction with wavelet transformation are: defining thresholding levels, level of decomposition and number of wavelet vanishing moment. In this analysis decomposition level and number of vanishing moments are defined via simulation for pure sinusoid signal, these values are used for signals with perturbations and they provide

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22

Lee, Jiann-Der, Yaw-Hwang Chiou, and Jing-Ming Guo. "Reversible Data Hiding Scheme with High Embedding Capacity Using Semi-Indicator-Free Strategy." Mathematical Problems in Engineering 2013 (2013): 1–11. http://dx.doi.org/10.1155/2013/476181.

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A novel reversible data-hiding scheme is proposed to embed secret data into a side-matched-vector-quantization- (SMVQ-) compressed image and achieve lossless reconstruction of a vector-quantization- (VQ-) compressed image. The rather random distributed histogram of a VQ-compressed image can be relocated to locations close to zero by SMVQ prediction. With this strategy, fewer bits can be utilized to encode SMVQ indices with very small values. Moreover, no indicator is required to encode these indices, which yields extrahiding space to hide secret data. Hence, high embedding capacity and low bit

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23

Ibrir, S., and S. Diop. "Robust state reconstruction of linear neutral-type delay systems with application to lossless transmission lines: a convex optimization approach." IMA Journal of Mathematical Control and Information 26, no. 3 (2009): 281–98. http://dx.doi.org/10.1093/imamci/dnp008.

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Liu, Shanyun, Rui She, Zheqi Zhu, and Pingyi Fan. "Storage Space Allocation Strategy for Digital Data with Message Importance." Entropy 22, no. 5 (2020): 591. http://dx.doi.org/10.3390/e22050591.

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This paper mainly focuses on the problem of lossy compression storage based on the data value that represents the subjective assessment of users when the storage size is still not enough after the conventional lossless data compression. To this end, we transform this problem to an optimization, which pursues the least importance-weighted reconstruction error in data reconstruction within limited total storage size, where the importance is adopted to characterize the data value from the viewpoint of users. Based on it, this paper puts forward an optimal allocation strategy in the storage of dig

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25

Suzuki, Taizo, and Hiroyuki Kudo. "2D Non-Separable Block-Lifting Structure and Its Application to $M$ -Channel Perfect Reconstruction Filter Banks for Lossy-to-Lossless Image Coding." IEEE Transactions on Image Processing 24, no. 12 (2015): 4943–51. http://dx.doi.org/10.1109/tip.2015.2472294.

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26

Abbaas, Douaa Younis. "Fractal Image Compression Based on High Entropy Values Technique." Al-Mustansiriyah Journal of Science 28, no. 2 (2018): 119. http://dx.doi.org/10.23851/mjs.v28i2.507.

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There are many attempts tried to improve the encoding stage of FIC because it consumed time. These attempts worked by reducing size of the search pool for pair range-domain matching but most of them led to get a bad quality, or a lower compression ratio of reconstructed image. This paper aims to present a method to improve performance of the full search algorithm by combining FIC (lossy compression) and another lossless technique (in this case entropy coding is used). The entropy technique will reduce size of the domain pool (i. e., number of domain blocks) based on the entropy value of each r

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Kelkar, Vishakha, Kushal Tuckley, and Hitesh Nemade. "Novel Variants of a Histogram Shift-Based Reversible Watermarking Technique for Medical Images to Improve Hiding Capacity." Journal of Healthcare Engineering 2017 (2017): 1–7. http://dx.doi.org/10.1155/2017/3538979.

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In telemedicine systems, critical medical data is shared on a public communication channel. This increases the risk of unauthorised access to patient’s information. This underlines the importance of secrecy and authentication for the medical data. This paper presents two innovative variations of classical histogram shift methods to increase the hiding capacity. The first technique divides the image into nonoverlapping blocks and embeds the watermark individually using the histogram method. The second method separates the region of interest and embeds the watermark only in the region of noninte

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Muñoz, G. Tejeda, M. del C. Grados Luyando, A. Fernández Téllez, M. Rodríguez Cahuantzi, M. I. Martínez Hernández, and B. De Celis Alonso. "Triggerless charge measurement system for fast characterization with APDs and PMTs." Revista Mexicana de Física 66, no. 4 Jul-Aug (2020): 475. http://dx.doi.org/10.31349/revmexfis.66.475.

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Particle detectors based on the response of sensitive material (plastic scintillator, saturated gas, etc.) usually need characterization and test procedures before final installation. Cosmic ray particles are normally used to perform those preliminary tests which includes a detailed inspection of the readout electronics and a data acquisition to obtain a charge distribution of cosmic ray detection.The Data Processing Interface is implemented in an FPGA (ALTERA family), designed to test the acquisition of digitized signals from light sensors, fotomultipliers (PMTs) and Avalanche photodiodes (AP

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Finley, Matthew G., and Tyler Bell. "Two-Channel 3D Range Geometry Compression with Virtual Plane Encoding." Electronic Imaging 2021, no. 18 (2021): 61–1. http://dx.doi.org/10.2352/issn.2470-1173.2021.18.3dia-061.

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Modern computing and imaging technologies have allowed for many recent advances to be made in the field of 3D range imaging: range data can now be acquired at speeds much faster than real-time, with sub-millimeter precision. However, these benefits come at the cost of an increased quantity of data being generated by 3D range imaging systems, potentially limiting the number of applications that can take advantage of this technology. One common approach to the compression of 3D range data is to encode it within the three color channels of a traditional 24-bit RGB image. This paper presents a nov

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Qin, Shiyue, Zhenhua Tan, Fucai Zhou, Jian Xu, and Zongye Zhang. "A Verifiable Steganography-Based Secret Image Sharing Scheme in 5G Networks." Security and Communication Networks 2021 (January 27, 2021): 1–14. http://dx.doi.org/10.1155/2021/6629726.

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With the development and innovation of new techniques for 5G, 5G networks can provide extremely large capacity, robust integrity, high bandwidth, and low latency for multimedia image sharing and storage. However, it will surely exacerbate the privacy problems intrinsic to image transformation. Due to the high security and reliability requirements for storing and sharing sensitive images in the 5G network environment, verifiable steganography-based secret image sharing (SIS) is attracting increasing attention. The verifiable capability is necessary to ensure the correct image reconstruction. Fr

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Tzagkarakis, George, Pavlos Charalampidis, Stylianos Roubakis, Antonis Makrogiannakis, and Panagiotis Tsakalides. "Quantifying the Computational Efficiency of Compressive Sensing in Smart Water Network Infrastructures." Sensors 20, no. 11 (2020): 3299. http://dx.doi.org/10.3390/s20113299.

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Monitoring contemporary water distribution networks (WDN) relies increasingly on smart metering technologies and wireless sensor network infrastructures. Smart meters and sensor nodes are deployed to capture and transfer information from the WDN to a control center for further analysis. Due to difficulties in accessing the water assets, many water utility companies employ battery-powered nodes, which restricts the use of high sampling rates, thus limiting the knowledge we can extract from the recorder data. To mitigate this issue, compressive sensing (CS) has been introduced as a powerful fram

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32

Amitava, Nag, Arup Kumar Chattopadhyay, and Maitra Paramita. "An Efficient (t,n) Threshold Secret Image Sharing Scheme Based on Thien-Lin Secret Image Sharing." American Journal of Advanced Computing 1, no. 4 (2020): 1–4. http://dx.doi.org/10.15864/ajac.1401.

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In a (t, n) threshold secret image sharing scheme (TSIS), a secret image is first encoded into n pieces, normally referred as shares or shadow images. Those share-images can be stored or transferred safely as individually a share-image cannot reveal any detail about the secret image. The receiver or user of the share-images referred as participants. If at least t(≤n) share-images are submitted by the participants, the secret image can be recomputed. One of the most popular secret image sharing schemes was proposed by Thien-Lin (2002). The authors had proposed two versions of the scheme. The fi

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33

Vitalis, Stelios, Ken Ohori, and Jantien Stoter. "Incorporating Topological Representation in 3D City Models." ISPRS International Journal of Geo-Information 8, no. 8 (2019): 347. http://dx.doi.org/10.3390/ijgi8080347.

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3D city models are being extensively used in applications such as evacuation scenarios and energy consumption estimation. The main standard for 3D city models is the CityGML data model which can be encoded through the CityJSON data format. CityGML and CityJSON use polygonal modelling in order to represent geometries. True topological data structures have proven to be more computationally efficient for geometric analysis compared to polygonal modelling. In a previous study, we have introduced a method to topologically reconstruct CityGML models while maintaining the semantic information of the

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34

Kliuchenia, V. V. "Design of a discrete сosine transformation processor for image compression systems on a losless-to-lossy circuit". Doklady BGUIR 19, № 3 (2021): 5–13. http://dx.doi.org/10.35596/1729-7648-2021-19-3-5-13.

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Today, mobile multimedia systems that use the H.261 / 3/4/5, MPEG-1/2/4 and JPEG standards for encoding / decoding video, audio and images are widely spread [1–4]. The core of these standards is the discrete cosine transform (DCT) of I, II, III ... VIII types [DCT]. Wide support in a huge number of multimedia applications of the JPEG format by circuitry and software solutions and the need for image coding according to the L2L scheme determines the relevance of the problem of creating a decorrelated transformation based on DCT and methods for rapid prototyping of processors for computing an int

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Draganov, Deyan, Kees Wapenaar, and Jan Thorbecke. "Seismic interferometry: Reconstructing the earth’s reflection response." GEOPHYSICS 71, no. 4 (2006): SI61—SI70. http://dx.doi.org/10.1190/1.2209947.

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In 1968, Jon Claerbout showed that the reflection response of a 1D acoustic medium can be reconstructed by autocorrelating the transmission response. Since then, several authors have derived relationships for reconstructing Green’s functions at the surface, using crosscorrelations of (noise) recordings that were taken at the surface and that derived from subsurface sources. For acoustic media, we review relations between the reflection response and the transmission response in 3D inhomogeneous lossless media. These relations are derived from a one-way wavefield reciprocity theorem. We use mode

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Al-Timimi, Rana Talib. "Bit Plane Slicing, Wavelet and Polynomials Mixing for Image Compression." Iraqi Journal of Science, November 27, 2019, 2497–505. http://dx.doi.org/10.24996/ijs.2019.60.11.22.

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This paper introduced a hybrid technique for lossless image compression of natural and medical images; it is based on integrating the bit plane slicing and Wavelet transform along with a mixed polynomial of linear and non linear base. The experiments showed high compression performance with fully grunted reconstruction.

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Huang, Wei, Yan Wang, and David W. Rosen. "Inverse Surfacelet Transform for Image Reconstruction With Constrained-Conjugate Gradient Methods." Journal of Computing and Information Science in Engineering 14, no. 2 (2014). http://dx.doi.org/10.1115/1.4026376.

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Image reconstruction is the transformation process from a reduced-order representation to the original image pixel form. In materials characterization, it can be utilized as a method to retrieve material composition information. In our previous work, a surfacelet transform was developed to efficiently represent boundary information in material images with surfacelet coefficients. In this paper, new constrained-conjugate-gradient based image reconstruction methods are proposed as the inverse surfacelet transform. With geometric constraints on boundaries and internal distributions of materials,

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