2020 International Conference on Signal Processing and Communications (SPCOM) 2020
DOI: 10.1109/spcom50965.2020.9179569
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Sparse Plane-wave Decomposition for Upscaling Ambisonic Signals

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Cited by 2 publications
(9 citation statements)
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“…This study constructs a framework for plane-wave decomposition by investigating the sparseness of the source signals. Further, we extend our earlier work [12,15] by exploring a diversity minimization class of algorithms called FOCUSS. Compared to frequency domain upscaling [7], this method's implementation in the time domain is also computationally efficient and applicable to broadband audio sources.…”
Section: Introductionmentioning
confidence: 86%
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“…This study constructs a framework for plane-wave decomposition by investigating the sparseness of the source signals. Further, we extend our earlier work [12,15] by exploring a diversity minimization class of algorithms called FOCUSS. Compared to frequency domain upscaling [7], this method's implementation in the time domain is also computationally efficient and applicable to broadband audio sources.…”
Section: Introductionmentioning
confidence: 86%
“…Using an emphasis operator [4][5][6] or increasing the order of encoded ambisonic signals [7][8][9][10][11][12][13][14][15][16][17] can improve spatial resolution. In [4,5], an objective estimator is built to localize sources while conserving energy.…”
Section: Introductionmentioning
confidence: 99%
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“…Another approach to enhance the Ambisonics signals is by upscaling, which aims to extend the spherical harmonics order, and leads to enhanced spatial resolution and higher-quality spatial audio signals. Earlier work includes the employment of compressed sensing [101][102][103] and sparse decomposition based on dictionary learning [104], while more recent work includes the employment of sparse recovery [105] and deep-learning [106][107][108]. Orderlimited Ambisonics signals translate to order truncation of the HRTF [109], which may have a detrimental effect on the perception of the reproduced binaural signals [93,110].…”
Section: Ambisonicsmentioning
confidence: 99%