2023 International Conference on Power, Instrumentation, Energy and Control (PIECON)

dc.contributor.authorChandra, Harshit
dc.contributor.authorBajpai, Shrish
dc.date.accessioned2024-01-17T09:13:23Z
dc.date.available2024-01-17T09:13:23Z
dc.date.issued2023
dc.description3D-Block Partitioning Embedded Coding for Hyperspectral Image Sensors by Harshit Chandra, Shrish Bajpaien_US
dc.description.abstractComputational 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.isbn979-8-3503-9976-9
dc.identifier.urihttps://ieeexplore.ieee.org/abstract/document/10085841
dc.identifier.urihttp://136.232.12.194:4000/handle/123456789/806
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectElectronics & Communication Engineeringen_US
dc.title2023 International Conference on Power, Instrumentation, Energy and Control (PIECON)en_US
dc.typeBook chapteren_US

Files

Original bundle

Now showing 1 - 1 of 1
Thumbnail Image
Name:
3D-Block Partitioning Embedded Coding for Hyperspectral Image Sensors - Copy.pdf
Size:
217.72 KB
Format:
Adobe Portable Document Format
Description:
IEEE

License bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description: