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QUANTIZED TENSOR ROBUST PRINCIPAL COMPONENT ANALYSIS

Abstract: 

High-dimensional data structures, known as tensors, are fundamental in many applications, including multispectral imaging and color video processing. Compression of such huge amount of multidimensional data collected over time is of paramount importance, necessitating the process of quantization of measurements into discrete values. Furthermore, noise and issues related to the acquisition and transmission of signals frequently lead to unobserved, lost or corrupted measurements. In this paper, we introduce a tensor robust principal component analysis algorithm in order to recover a tensor with real-valued entries from a partly observed set of quantized and sparsely corrupted entries. We formulate the problem as a constrained maximum likelihood estimation of the sum of a low-rank tensor and a sparse tensor, through matricizations in each mode, in combination with a quantization and statistical measurement model. Experimental results on satellite derived land surface time-series demonstrate that directly operating with the quantized measurements, rather than treating them as real values, results in a low recovery error, while the proposed method is also capable of detecting temperature anomalies (e.g., forest fires).

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Paper Details

Authors:
Anastasia Aidini, Grigorios Tsagkatakis, Panagiotis Tsakalides
Submitted On:
14 May 2020 - 7:54am
Short Link:
Type:
Presentation Slides
Event:
Document Year:
2020
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QTRPCA_presentation.pdf

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[1] Anastasia Aidini, Grigorios Tsagkatakis, Panagiotis Tsakalides, "QUANTIZED TENSOR ROBUST PRINCIPAL COMPONENT ANALYSIS", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5288. Accessed: Aug. 10, 2020.
@article{5288-20,
url = {http://sigport.org/5288},
author = {Anastasia Aidini; Grigorios Tsagkatakis; Panagiotis Tsakalides },
publisher = {IEEE SigPort},
title = {QUANTIZED TENSOR ROBUST PRINCIPAL COMPONENT ANALYSIS},
year = {2020} }
TY - EJOUR
T1 - QUANTIZED TENSOR ROBUST PRINCIPAL COMPONENT ANALYSIS
AU - Anastasia Aidini; Grigorios Tsagkatakis; Panagiotis Tsakalides
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5288
ER -
Anastasia Aidini, Grigorios Tsagkatakis, Panagiotis Tsakalides. (2020). QUANTIZED TENSOR ROBUST PRINCIPAL COMPONENT ANALYSIS. IEEE SigPort. http://sigport.org/5288
Anastasia Aidini, Grigorios Tsagkatakis, Panagiotis Tsakalides, 2020. QUANTIZED TENSOR ROBUST PRINCIPAL COMPONENT ANALYSIS. Available at: http://sigport.org/5288.
Anastasia Aidini, Grigorios Tsagkatakis, Panagiotis Tsakalides. (2020). "QUANTIZED TENSOR ROBUST PRINCIPAL COMPONENT ANALYSIS." Web.
1. Anastasia Aidini, Grigorios Tsagkatakis, Panagiotis Tsakalides. QUANTIZED TENSOR ROBUST PRINCIPAL COMPONENT ANALYSIS [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5288