Research on Lossless Compression Coding Algorithm of N-Band Parametric Spectral Integer Reversible Transformation Combined With the Lifting Scheme for Hyperspectral Images-Reference-Cited by-同舟云学术

Research on Lossless Compression Coding Algorithm of N-Band Parametric Spectral Integer Reversible Transformation Combined With the Lifting Scheme for Hyperspectral Images

Published:2022 Issue: Volume:10 Page:88632-88643
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Li Changcheng¹^ORCID,Chen Deyun¹^ORCID,Xie Chengjun²,Gao Yilong³,Liu Jinrui⁴

Affiliation:

1. School of Computer Science and Technology, Harbin University of Science and Technology, Harbin, China

2. School of Computer Science and Technology, Beihua University, Jilin City, China

3. School of Information Science and Engineering, Linyi University, Linyi, China

4. School of Electrical and Information Engineering, Jilin Agricultural Science and Technology University, Jilin City, China

Funder

Natural Science Foundation of China

Key Scientific Research Project of Jilin Provincial Department of Education

Key Project of Jilin Provincial Science and Technology Department

Project for Science and Technology Center and Science and Technology Service Platform

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09861627.pdf?arnumber=9861627

Reference34 articles.

1. Replacing missing values in the standard Multi-angle Imaging SpectroRadiometer (MISR) radiometric camera-by-camera cloud mask (RCCM) data product

2. Mosaic-Based Color-Transform Optimization for Lossy and Lossy-to-Lossless Compression of Pathology Whole-Slide Images

3. Lossless CFA Image Compression Chip Design for Wireless Capsule Endoscopy

4. An innovative design of a hybrid chain coding algorithm for bi-level image compression using an agent-based modeling approach

5. Model-Free Lossless Data Compression for Real-Time Low-Latency Transmission in Smart Grids

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