A novel method to reduce speckle in SAR images

Chen, Rensheng; Guo, Huadong; Dian, Fan

doi:10.1080/01431160210153110

Cited by 49 publications

(8 citation statements)

References 6 publications

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“…Nevertheless, the 2-D method has been applied already. Examples of geophysical applications have been reported by Han et al [2002], where they used the method to reduce speckle in synthetic aperture radar images, and by Sinclair and Pegram [2005], where they used the EMD for temporal-spatial rainfall data.…”

Section: Two-dimensional Emdmentioning

confidence: 99%

A review on Hilbert‐Huang transform: Method and its applications to geophysical studies

Huang

2008

Reviews of Geophysics

1,551

1,040

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[1] Data analysis has been one of the core activities in scientific research, but limited by the availability of analysis methods in the past, data analysis was often relegated to data processing. To accommodate the variety of data generated by nonlinear and nonstationary processes in nature, the analysis method would have to be adaptive. Hilbert-Huang transform, consisting of empirical mode decomposition and Hilbert spectral analysis, is a newly developed adaptive data analysis method, which has been used extensively in geophysical research. In this review, we will briefly introduce the method, list some recent developments, demonstrate the usefulness of the method, summarize some applications in various geophysical research areas, and finally, discuss the outstanding open problems. We hope this review will serve as an introduction of the method for those new to the concepts, as well as a summary of the present frontiers of its applications for experienced research scientists.

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Section: Two-dimensional Emdmentioning

confidence: 99%

A review on Hilbert‐Huang transform: Method and its applications to geophysical studies

Huang

2008

Reviews of Geophysics

1,551

1,040

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“…EMD [23], originally developed for nonlinear and non-smooth signals, posits that each signal consists of distinct eigenmode functions, each of which exhibits potential linearity or nonlinearity. Subsequently, researchers have extended the application of EMD to various domains, including image processing [24][25][26].…”

Section: Empirical Mode Decomposition Topologically Associated Domainmentioning

confidence: 99%

An Empirical Mode Decomposition-Based Method to Identify Topologically Associated Domains from Chromatin Interactions

Zhao,

Duan,

Yao

2023

Electronics

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Topologically associated domains (TADs) represent essential units constituting chromatin’s intricate three-dimensional spatial organization. TADs are stably present across cell types and species, and their influence on vital biological processes, such as gene expression, DNA replication, and chromosomal translocation, underscores their significance. Accordingly, the identification of TADs within the Hi-C interaction matrix is a key point in three-dimensional genomics. TADs manifest as contiguous blocks along the diagonal of the Hi-C interaction matrix, which are characterized by dense interactions within blocks and sparse interactions between blocks. An optimization method is proposed to enhance Hi-C interaction matrix data using the empirical mode decomposition method, which requires no prior knowledge and adaptively decomposes Hi-C data into a sum of multiple eigenmodal functions via exploiting the inherent characteristics of variations in the input Hi-C data. We identify TADs within the optimized data and compared the results with five commonly used TAD detection methods, namely the Directionality Index (DI), Interaction Isolation (IS), HiCKey, HiCDB, and TopDom. The results demonstrate the universality and efficiency of the proposed method, highlighting its potential as a valuable tool in TAD identification.

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“…The EMD is based on the sequential extraction of energy associated with various intrinsic time scales of the signal, called Intrinsic Mode Functions (IMF). The EMD has received more attention in terms of interpretations [10,11], improvement [1,[12][13][14], Time-Frequency Analysis [15][16][17], denoising [18,19], Speech enhancement [20], and Radar field [21][22][23][24][25] . .…”

Section: Introductionmentioning

confidence: 99%

ISAR image formation with a combined empirical mode decomposition and time frequency representation

Ahmed¹,

Cexus²,

Toumi³

2015

2015 23rd European Signal Processing Conference (EUSIPCO)

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In this paper, a method for Inverse Synthetic Aperture Radar (ISAR) image formation based on the use of the Complex Empirical Mode Decomposition (CEMD) is proposed. The CEMD [1] which based on the Empirical Mode Decomposition (EMD) is used in conjunction with a Time-Frequency Representation (TFR) to estimate a 3-D time-range-Doppler Cubic image, which we can use to effectively extract a sequence of ISAR 2-D range-Doppler images. The potential of the proposed method to construct ISAR image is illustrated by simulations results performed on synthetic data and compared to 2-D Fourier Transform and TFR methods. The simulation results indicate that this method can provide ISAR images with a good resolution. These results demonstrate the potential application of the proposed method for ISAR image formation.

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A novel method to reduce speckle in SAR images

Cited by 49 publications

References 6 publications

A review on Hilbert‐Huang transform: Method and its applications to geophysical studies

A review on Hilbert‐Huang transform: Method and its applications to geophysical studies

An Empirical Mode Decomposition-Based Method to Identify Topologically Associated Domains from Chromatin Interactions

ISAR image formation with a combined empirical mode decomposition and time frequency representation

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