Paper Info
Title
Entropy Based Sub-band Deletion for Multispectral Image Compression.
Abstract
This paper proposes effective and efficient multispectral image compression targeting at reducing the extent of storage and transmission time, and at the same time retaining a quality of the reconstructed images. The proposed method is relying on deleting a sub band before compressing the multispectral image. The deleted sub-band is based on the entropy value of each band. Discrete wavelet transform is applied to bands of multispectral image having highest entropy value to delete a sub-band among the four sub-bands and the retained subbands are followed by entropy coder for compression. Furthermore, we exploit JPEG2000+principal component analysis (PCA) to more compress the remaining bands. We used multispectral images from NASA website to validate our proposed method. Experimental result on designated dataset reveals that our proposed method improves the reconstructed image quality better than JPEG2000, SPHIT and some other methods in PSNR and SAM metrics.
Year
DOI
Venue
2017
10.1007/978-3-319-77383-4_77
ADVANCES IN MULTIMEDIA INFORMATION PROCESSING - PCM 2017, PT II
Keywords
Field
DocType
Image compression,Sub-band deletion,Wavelet transform,Entropy
Computer vision,Pattern recognition,Computer science,Multispectral image,Image quality,Discrete wavelet transform,Artificial intelligence,JPEG 2000,Transmission time,Image compression,Principal component analysis,Wavelet transform
Conference
Volume
ISSN
Citations 
10736
0302-9743
0
PageRank 
References 
Authors
0.34
6
7
Name
Order
Citations
PageRank
Worku J. Sori1202.89
Dongyang Zhao246.49
Lou Fang300.34
Fu Yunsheng400.34
Liu Shaohui501.01
Feng Jiang630437.75
Adil Khan72211.68