2023 International Conference on Power, Instrumentation, Energy and Control (PIECON)
dc.contributor.author | Chandra, Harshit | |
dc.contributor.author | Bajpai, Shrish | |
dc.date.accessioned | 2024-01-17T09:13:23Z | |
dc.date.available | 2024-01-17T09:13:23Z | |
dc.date.issued | 2023 | |
dc.description | 3D-Block Partitioning Embedded Coding for Hyperspectral Image Sensors by Harshit Chandra, Shrish Bajpai | en_US |
dc.description.abstract | Computational complexity with the coding efficiency of any hyperspectral image sensor is a challenging issue. 3D-SPIHT has reasonable complexity and generates an embedded bit-stream. Due to the linked lists, the processing of the compression through the 3D-SPIHT gets slow at the high bit rates. This manuscript presents a low-complexity version of 3D-SPIHT which uses the array structure instead of linked lists. These arrays are independent of each other. The coding memory required by the arrays is the same as the linked list used in 3D-SPIHT. Through the use of array, the coding complexity is reduced and coding efficiency is increased with the use of parity of the bit plane. Thus, the proposed compression scheme is an optimum solution for the resource-constraint hyperspectral image sensor. | en_US |
dc.identifier.isbn | 979-8-3503-9976-9 | |
dc.identifier.uri | https://ieeexplore.ieee.org/abstract/document/10085841 | |
dc.identifier.uri | http://136.232.12.194:4000/handle/123456789/806 | |
dc.language.iso | en | en_US |
dc.publisher | IEEE | en_US |
dc.subject | Electronics & Communication Engineering | en_US |
dc.title | 2023 International Conference on Power, Instrumentation, Energy and Control (PIECON) | en_US |
dc.type | Book chapter | en_US |
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