Pan-Sharpening for Spectral Details Preservation Via Convolutional Sparse Coding in Non-Subsampled Shearlet Space

2021 ◽  
Author(s):  
Dhara J. Sangani ◽  
Rajesh A. Thakker ◽  
S. D. Panchal ◽  
Rajesh Gogineni
Keyword(s):  
Sparse Coding ◽  
Low Frequency ◽  
Frequency Bands ◽  
Adaptive Weights ◽  
Remote Sensing Image Fusion ◽  
Fused Image ◽  
Satellite Sensors ◽  
Quantitative Results ◽  
Image Fusion Technique ◽  
Iterative Filtering

The optical satellite sensors encounter certain constraints on producing high-resolution multispectral (HRMS) images. Pan-sharpening (PS) is a remote sensing image fusion technique, which is an effective mechanism to overcome the limitations of available imaging products. The prevalent issue in PS algorithms is the imbalance between spatial quality and spectral details preservation, thereby producing intensity variations in the fused image. In this paper, a PS method is proposed based on convolutional sparse coding (CSC) implemented in the non-subsampled shearlet transform (NSST) domain. The source images, panchromatic (PAN) and multispectral (MS) images, are decomposed using NSST. The resultant high-frequency bands are fused using adaptive weights determined from chaotic grey wolf optimization (CGWO) algorithm. The CSC-based model is employed to fuse the low-frequency bands. Further, an iterative filtering mechanism is developed to enhance the quality of fused image. Four datasets with different geographical content like urban area, vegetation, etc. and eight existing algorithms are used for evaluation of the proposed PS method. The comprehensive visual and quantitative results approve that the proposed method accomplishes considerable improvement in spatial and spectral details equivalence in the pan-sharpened image.

Infrared and Visible Remote Sensing Imagery Fusion Based on Fuzzy Logic and NSCT

2011 ◽  
Vol 148-149 ◽  
pp. 158-162
Author(s):  
Qing Qing Huang ◽  
Jian Yang ◽  
Yuan Ji
Keyword(s):  
Remote Sensing ◽  
Fuzzy Logic ◽  
Low Frequency ◽  
Scale Analysis ◽  
Nonsubsampled Contourlet Transform ◽  
Analysis Method ◽  
Remote Sensing Imagery ◽  
Multi Scale ◽  
Remote Sensing Image Fusion ◽  
Fused Image

Although average or region energy method are widely used in calculating low-frequency coefficients in multi-sensor fusion, these methods still have shortcomings while fusing infrared and visible remote sensing imagery. Because of the differences of infrared and visible imaging mechanism, the extent of each source image’s contribution to the fused image is uncertain. Much information could be reduced and good result can not be obtained. Fuzzy logic is an efficient way to resolve uncertain problems. Therefore, fuzzy logic and nonsubsampled Contourlet transform (NSCT) are introduced into infrared and visible remote sensing image fusion and a novel multi-scale analysis method based on fuzzy logic is proposed in this paper. The spatial detail information of fused results is improved and the experiment indicates that the proposed method can get better visual quality.

scholarly journals Multi-focus Image Fusion Using an Effective Discrete Wavelet Transform Based Algorithm

2014 ◽  
Vol 14 (2) ◽  
pp. 102-108 ◽  
Author(s):  
Yong Yang ◽  
Shuying Huang ◽  
Junfeng Gao ◽  
Zhongsheng Qian
Keyword(s):  
Wavelet Transform ◽  
Image Fusion ◽  
Discrete Wavelet Transform ◽  
High Frequency ◽  
Low Frequency ◽  
Objective Evaluation ◽  
Discrete Wavelet ◽  
Evaluation Indexes ◽  
Fused Image ◽  
Focus Image

Abstract In this paper, by considering the main objective of multi-focus image fusion and the physical meaning of wavelet coefficients, a discrete wavelet transform (DWT) based fusion technique with a novel coefficients selection algorithm is presented. After the source images are decomposed by DWT, two different window-based fusion rules are separately employed to combine the low frequency and high frequency coefficients. In the method, the coefficients in the low frequency domain with maximum sharpness focus measure are selected as coefficients of the fused image, and a maximum neighboring energy based fusion scheme is proposed to select high frequency sub-bands coefficients. In order to guarantee the homogeneity of the resultant fused image, a consistency verification procedure is applied to the combined coefficients. The performance assessment of the proposed method was conducted in both synthetic and real multi-focus images. Experimental results demonstrate that the proposed method can achieve better visual quality and objective evaluation indexes than several existing fusion methods, thus being an effective multi-focus image fusion method.

scholarly journals Spillovers of Stock Markets among the BRICS: New Evidence in Time and Frequency Domains before the Outbreak of COVID-19 Pandemic

2021 ◽  
Vol 14 (3) ◽  
pp. 112
Author(s):  
Kai Shi
Keyword(s):  
Stock Market ◽  
Frequency Band ◽  
Stock Markets ◽  
Emerging Market ◽  
Low Frequency ◽  
Systematic Risk ◽  
Error Variance ◽  
Frequency Bands ◽  
Volatility Spillovers ◽  
Risk Sources

We attempted to comprehensively decode the connectedness among the abbreviation of five emerging market countries (BRICS) stock markets between 1 August 2002 and 31 December 2019 not only in time domain but also in frequency domain. A continuously varying spillover index based on forecasting error variance decomposition within a generalized abbreviation of vector-autoregression (VAR) framework was computed. With the help of spectral representation, heterogeneous frequency responses to shocks were separated into frequency-specific spillovers in five different frequency bands to reveal differentiated linkages among BRICS markets. Rolling sample analyses were introduced to allow for multiple changes during the sample period. It is found that return spillovers dominated by the high frequency band (within 1 week) part declined with the drop of frequencies, while volatility spillovers dominated by the low frequency band (above 1 quarter) part grew with the decline in frequencies; the dynamics of spillovers were influenced by crucial systematic risk events, and some similarities implied in the spillover dynamics in different frequency bands were found. From the perspective of identifying systematic risk sources, China’s stock market and Russia’s stock market, respectively, played an influential role for return spillover and volatility spillover across BRICS markets.

An Effective Brain Imaging Biomarker for AD and aMCI: ALFF in Slow-5 Frequency Band

2021 ◽  
Vol 18 ◽  
Author(s):  
Luoyu Wang ◽  
Qi Feng ◽  
Mei Wang ◽  
Tingting Zhu ◽  
Enyan Yu ◽  
...  
Keyword(s):  
Brain Imaging ◽  
Frequency Band ◽  
Low Frequency ◽  
Posterior Cingulate Cortex ◽  
Angular Gyrus ◽  
Imaging Biomarker ◽  
Support Vector ◽  
Frequency Bands ◽  
Local Functional ◽  
Left Angular Gyrus

Background: As a potential brain imaging biomarker, amplitude of low frequency fluc-tuation (ALFF) has been used as a feature to distinguish patients with Alzheimer’s disease (AD) and amnestic mild cognitive impairment (aMCI) from normal controls (NC). However, it remains unclear whether the frequency-dependent pattern of ALFF alterations can effectively distinguish the different phases of the disease. Methods: In the present study, 52 AD and 50 aMCI patients were enrolled together with 43 NC in total. The ALFF values were calculated in the following three frequency bands: classical (0.01-0.08 Hz), slow-4 (0.027-0.073 Hz) and slow-5 (0.01-0.027 Hz) for the three different groups. Subsequently, the local functional abnormalities were employed as features to examine the effect of classification among AD, aMCI and NC using a support vector machine (SVM). Results: We found that the among-group differences of ALFF in the different frequency bands were mainly located in the left hippocampus (HP), right HP, bilateral posterior cingulate cortex (PCC) and bilateral precuneus (PCu), left angular gyrus (AG) and left medial prefrontal cortex (mPFC). When the local functional abnormalities were employed as features, we identified that the ALFF in the slow-5 frequency band showed the highest accuracy to distinguish among the three groups. Conclusion: These findings may deepen our understanding of the pathogenesis of AD and suggest that slow-5 frequency band may be helpful to explore the pathogenesis and distinguish the phases of this disease.

scholarly journals Disparity in interaural time difference improves the accuracy of neural representations of individual concurrent narrowband sounds in rat inferior colliculus and auditory cortex

2020 ◽  
Vol 123 (2) ◽  
pp. 695-706
Author(s):  
Lu Luo ◽  
Na Xu ◽  
Qian Wang ◽  
Liang Li
Keyword(s):  
Auditory Cortex ◽  
Inferior Colliculus ◽  
Interaural Time Difference ◽  
Critical Role ◽  
Low Frequency ◽  
Time Difference ◽  
Neural Representation ◽  
Frequency Bands ◽  
Neural Segregation ◽  
Peripheral Auditory System

The central mechanisms underlying binaural unmasking for spectrally overlapping concurrent sounds, which are unresolved in the peripheral auditory system, remain largely unknown. In this study, frequency-following responses (FFRs) to two binaurally presented independent narrowband noises (NBNs) with overlapping spectra were recorded simultaneously in the inferior colliculus (IC) and auditory cortex (AC) in anesthetized rats. The results showed that for both IC FFRs and AC FFRs, introducing an interaural time difference (ITD) disparity between the two concurrent NBNs enhanced the representation fidelity, reflected by the increased coherence between the responses evoked by double-NBN stimulation and the responses evoked by single NBNs. The ITD disparity effect varied across frequency bands, being more marked for higher frequency bands in the IC and lower frequency bands in the AC. Moreover, the coherence between IC responses and AC responses was also enhanced by the ITD disparity, and the enhancement was most prominent for low-frequency bands and the IC and the AC on the same side. These results suggest a critical role of the ITD cue in the neural segregation of spectrotemporally overlapping sounds. NEW & NOTEWORTHY When two spectrally overlapped narrowband noises are presented at the same time with the same sound-pressure level, they mask each other. Introducing a disparity in interaural time difference between these two narrowband noises improves the accuracy of the neural representation of individual sounds in both the inferior colliculus and the auditory cortex. The lower frequency signal transformation from the inferior colliculus to the auditory cortex on the same side is also enhanced, showing the effect of binaural unmasking.

Methyl Isocyanide: The Low-Frequency Bands ν8 and ν7, and a Determination of the Rotational Constant A0

1995 ◽  
Vol 173 (2) ◽  
pp. 423-430 ◽  
Author(s):  
J. Pliva ◽  
L.D. Le ◽  
J.W.C. Johns ◽  
Z. Lu ◽  
R.A. Bernheim
Keyword(s):  
Low Frequency ◽  
Rotational Constant ◽  
Frequency Bands ◽  
Methyl Isocyanide

scholarly journals Multimodal Medical Image Fusion using Guided Filter in NSCT Domain

2018 ◽  
Vol 11 (4) ◽  
pp. 1937-1946
Author(s):  
Nancy Mehta ◽  
Sumit Budhiraja
Keyword(s):  
Image Fusion ◽  
Medical Image ◽  
Similarity Index ◽  
Low Frequency ◽  
Structural Similarity ◽  
Relevant Information ◽  
Phase Congruency ◽  
Edge Preserving ◽  
Medical Image Fusion ◽  
Fused Image

Multimodal medical image fusion aims at minimizing the redundancy and collecting the relevant information using the input images acquired from different medical sensors. The main goal is to produce a single fused image having more information and has higher efficiency for medical applications. In this paper modified fusion method has been proposed in which NSCT decomposition is used to decompose the wavelet coefficients obtained after wavelet decomposition. NSCT being multidirectional,shift invariant transform provide better results.Guided filter has been used for the fusion of high frequency coefficients on account of its edge preserving property. Phase congruency is used for the fusion of low frequency coefficients due to its insensitivity to illumination contrast hence making it suitable for medical images. The simulated results show that the proposed technique shows better performance in terms of entropy, structural similarity index, Piella metric. The fusion response of the proposed technique is also compared with other fusion approaches; proving the effectiveness of the obtained fusion results.

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