NDLI: Complex SAR Image Compression Using Entropy-Constrained Dictionary Learning and Universal Trellis Coded Quantization

Content Provider	IET Digital Library
Author	Zhan, Xin Zhang, Rong
Abstract	In this paper, an Entropy-constrained dictionary learning algorithm (ECDLA) is introduced for efficient compression of Synthetic aperture radar (SAR) complex images. ECDLA RI encodes the Real and imaginary parts of the images using ECDLA and sparse representation, and ECDLA AP encodes the Amplitude and phase parts respectively. When compared with the compression method based on the traditional Dictionary learning algorithm (DLA), ECDLA RI improves the Signal-to-noise ratio (SNR) up to 0.66dB and reduces the Mean phase error (MPE) up to 0.0735 than DLA RI. With the same MPE, ECDLA AP outperforms DLA AP by up to 0.87dB in SNR. Furthermore, the proposed method is also suitable for real-time applications.
Starting Page	686
Ending Page	691
Page Count	6
ISSN	10224653
Volume Number	25
e-ISSN	20755597
Issue Number	Issue 4, Jul (2016)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/cje/25/4
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/cje.2016.07.015
Journal	Chinese Journal of Electronics
Publisher Date	2016-07-01
Access Restriction	Open
Rights Holder	© Chinese Institute of Electronics
Subject Keyword	Code Complex SAR Image Compression Data Compression ECDLA AP ECDLA RI Entropy-constrained Dictionary Learning Algorithm Mean Phase Error Quantisation (signal) Radar Equipment Radar Imaging Signal Processing And Detection Sparse Representation Synthetic Aperture Radar System And Application Trellis Code Universal Trellis Coded Quantization
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Electrical and Electronic Engineering

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