SAR polar format implementation with MATLAB

Author

Agrawal, Navneet ; Venugopalan, K.

Author_Institution

Deptt. of ECE, MPUAT, Udaipur

fYear

2008

fDate

21-24 Nov. 2008

Firstpage

889

Lastpage

891

Abstract

Transform coding based on the Karhunen-Loeve transform (KLT), the discrete cosine transform (DCT), and the discrete wavelet transform (DWT) is well-understood for optical images. Transform coding applied to synthetic aperture radar (SAR) data, however, has not been well studied. This paper shows the results of compressing SAR images when it is available in polar formats. We compare the compression results based on six performance criteria-mean-squared error (MSE), mean absolute error, peak signal-to-noise ratio (SNR), energy compaction, transform gain, and compression ratio (CR).

Keywords

Karhunen-Loeve transforms; discrete cosine transforms; discrete wavelet transforms; electrical engineering computing; image coding; mathematics computing; optical images; radar imaging; synthetic aperture radar; transform coding; DCT; DWT; KLT; Karhunen-Loeve transform; MATLAB; SAR polar format implementation; discrete cosine transform; discrete wavelet transform; image compression; optical images; synthetic aperture radar; transform coding; Adaptive optics; Compaction; Discrete cosine transforms; Discrete wavelet transforms; Image coding; Karhunen-Loeve transforms; MATLAB; PSNR; Synthetic aperture radar; Transform coding; Block Adaptive Quantizations; Data compression; Discrete Cosine Transform; Polar Format; Synthetic Aperture Radar;

fLanguage

English

Publisher

ieee

Conference_Titel

Recent Advances in Microwave Theory and Applications, 2008. MICROWAVE 2008. International Conference on

Conference_Location

Jaipur

Print_ISBN

978-1-4244-2690-4

Electronic_ISBN

978-1-4244-2691-1

Type

conf

DOI

10.1109/AMTA.2008.4763188

Filename

4763188