Study on Image Compression and Fusion Based on the Wavelet Transform Technology

Zhang, Ning; Zhu, Jiasong

doi:10.21307/ijssis-2017-768

Cited by 6 publications

(3 citation statements)

References 20 publications

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“…It can be inversely transformed according to the required accuracy and reconstructed to restore the approximate original data result. Compression fusion is an important means to realize data visualization, and data visualization is the main method of data research and analysis [32].…”

Section: Classification Of Multisensor Data Fusionmentioning

confidence: 99%

A New View of Multisensor Data Fusion: Research on Generalized Fusion

Chen

Liu

et al. 2021

Mathematical Problems in Engineering

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Multisensor data generalized fusion algorithm is a kind of symbolic computing model with multiple application objects based on sensor generalized integration. It is the theoretical basis of numerical fusion. This paper aims to comprehensively review the generalized fusion algorithms of multisensor data. Firstly, the development and definition of multisensor data fusion are analyzed and the definition of multisensor data generalized fusion is given. Secondly, the classification of multisensor data fusion is discussed, and the generalized integration structure of multisensor and its data acquisition and representation are given, abandoning the research characteristics of object oriented. Then, the principle and architecture of multisensor data fusion are analyzed, and a generalized multisensor data fusion model is presented based on the JDL model. Finally, according to the multisensor data generalized fusion architecture, some related theories and methods are reviewed, and the tensor-based multisensor heterogeneous data generalized fusion algorithm is proposed, and the future work is prospected.

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Section: Classification Of Multisensor Data Fusionmentioning

confidence: 99%

A New View of Multisensor Data Fusion: Research on Generalized Fusion

Chen

Liu

et al. 2021

Mathematical Problems in Engineering

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“…The Wavelet Transform (WT) has been proven very useful in many fields due to the ability of wavelets to resolve localized signal content in both scale and space [1][2][3][4][5]. The conventional method of implementing WT is by means of digital signal processing systems (DSP) with the required A/D or D/A converters.…”

Section: Introductionmentioning

confidence: 99%

“…Some experiments were conducted upon constructing three sorts of optimal analog wavelet bases with various orders. The experimental result data of Gauss-like analog wavelet, Morlet-like analog wavelet, and Marr-like analog wavelet are given in Tab [4][5][6].…”

mentioning

confidence: 99%

Optimal Analog Wavelet Bases Construction Using Hybrid Optimization Algorithm

Sun

2016

International Journal on Smart Sensing and Intelligent Systems

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An approach for the construction of optimal analog wavelet bases is presented. First, the definition of an analog wavelet is given. Based on the definition and the least-squares error criterion, a general framework for designing optimal analog wavelet bases is established, which is one of difficult nonlinear constrained optimization problems. Then, to solve this problem, a hybrid algorithm by combining chaotic map particle swarm optimization (CPSO) with local sequential quadratic programming (SQP) is proposed. CPSO is an improved PSO in which the saw tooth chaotic map is used to raise its global search ability. CPSO is a global optimizer to search the estimates of the global solution, while the SQP is employed for the local search and refining the estimates. Benefiting from good global search ability of CPSO and powerful local search ability of SQP, a high-precision global optimum in this problem can be gained. Finally, a series of optimal analog wavelet bases are constructed using the hybrid algorithm. The proposed method is tested for various wavelet bases and the improved performance is compared with previous works.

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Wireless Communication Systems: Compression and Decompression Algorithms

Mohamed

2022

Synthesis Lectures on Engineering, Science, and Technology

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Study on Image Compression and Fusion Based on the Wavelet Transform Technology

Cited by 6 publications

References 20 publications

A New View of Multisensor Data Fusion: Research on Generalized Fusion

A New View of Multisensor Data Fusion: Research on Generalized Fusion

Optimal Analog Wavelet Bases Construction Using Hybrid Optimization Algorithm

Wireless Communication Systems: Compression and Decompression Algorithms

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