Title:
Multi-Layer Dictionary Learning Using Low-Rank Updates
Multi-Layer Dictionary Learning Using Low-Rank Updates
Author(s)
Richert, Lee
Advisor(s)
Anderson, David V.
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Abstract
This dissertation presents a novel convolutional dictionary
learning algorithm for signals with a large number of channels.
This algorithm uses low-rank updates for the dictionary, so that
a matrix decomposition necessary for pursuit can be updated
efficiently. In later chapters, this algorithm is applied to
multi-layer dictionary models with multi-channel dictionaries and
single-channel coefficients, where the number of filters in one
layer is the number of channels in the subsequent dictionary
layer. This architecture is demonstrated on the task of JPEG
compression artifact removal.
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Date Issued
2022-01-04
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Resource Type
Text
Resource Subtype
Dissertation