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Low Complexity and Low Memory Compression Algorithm for Hyperspectral Image Sensors

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Abstract

The 3D-zero memory set partitioned embedded block (3D-ZM-SPECK) is an embedded and memory-efficient compression algorithm. Through, the 3D-ZM-SPECK does not require any coding memory, but testing of the sets for each bit-plane increases the complexity significantly which led a big constrain for the low resource HS image sensors. The proposed HS image compression algorithm is the low complexity solution of 3D-ZM-SPECK which reduces the recursive significance test of sets. Simulation results demonstrate that the proposed 3D-M-ZM-SPECK significantly reduces the complexity by ~ 25% with the other state of art HS image compression algorithms. Thus, it is a viable option for the HS image sensors.

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Acknowledgements

I am sincerely thankful to the anonymous reviewers for their critical comments and suggestions to improve the quality of the paper. The author wants to express his gratitude to Integral University, Lucknow, Uttar Pradesh, India for providing manuscript number IU/R&D/2023-MCN0001887 for the present research work.

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  1. Electronics and Communication Engineering Department, Faculty of Engineering and Information Technology, Integral University, Uttar Pradesh, Lucknow, India

    Shrish Bajpai

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Bajpai, S. Low Complexity and Low Memory Compression Algorithm for Hyperspectral Image Sensors. Wireless Pers Commun 131, 805–833 (2023). https://doi.org/10.1007/s11277-023-10455-8

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