Low complexity image coding technique for hyperspectral image sensors
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-023-14738-x.pdf
Reference58 articles.
1. Bajpai S, Singh HV, Kidwai NR (2017) Feature extraction & classification of hyperspectral images using singular spectrum analysis & multinomial logistic regression classifiers. In: IEEE international conference on multimedia, signal processing and communication technologies (IMPACT) Aligarh, India, pp 97–100. https://doi.org/10.1109/MSPCT.2017.8363982
2. Bajpai S, Singh HV, Kidwai NR (2019) 3D modified wavelet block tree coding for hyperspectral images. Indones J Electr Eng Comput Sci (IJEECS) 15(2):1001–1008. https://doi.org/10.11591/ijeecs.v15.i2.pp1001-1008
3. Bajpai S, Singh HV, Kidwai NR (2019) 3D Wavelet Block Tree Coding for Hyperspectral Images. Int J Innov Technol Exploring Eng 8(6C):64–68 ISSN: 2278–3075. https://www.ijitee.org/wp-content/uploads/papers/v8i6c/F12200486C19.pdf. Accessed 28 Feb 2022.
4. Bajpai S, Kidwai NR, Singh HV, Singh AK (2019) Low memory block tree coding for hyperspectral images. Multimed Tools Appl 78(19):27193–27209. https://doi.org/10.1007/s11042-019-07797-6
5. Bajpai S, Kidwai NR, Singh HV, Singh AK (2022) A low complexity hyperspectral image compression through 3D set partitioned embedded zero block coding. Multimed Tools Appl 81(1):841–872. https://doi.org/10.1007/s11042-021-11456-0
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