Convolutional Analysis Sparse Coding for Multimodal Image Super-Resolution

With multimodal imaging systems in place, recent research focus has been directed toward exploiting the knowledge from different imaging modalities to solve inverse problems, one example being image super-resolution, considered in this letter. The goal of multimodal image super-resolution (MISR) is...

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Veröffentlicht in:	IEEE sensors letters Jg. 8; H. 6; S. 1 - 4
Hauptverfasser:	Kumar, Kriti, Majumdar, Angshul, Kumar, A. Anil, Chandra, M. Girish
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 01.06.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Artificial neural networks Benchmark testing Convolutional codes convolutional sparse coding convolutional transform learning (CTL) Image coding Image enhancement Image reconstruction Image resolution Inverse problems joint optimization Learning multimodal image super-resolution (MISR) Performance enhancement Sensor applications Superresolution Task analysis Transforms
ISSN:	2475-1472, 2475-1472
Online-Zugang:	Volltext
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