An Improved Technique for Complex SAR Image Compression Based on FFT and Discrete Wavelet Transform

Abstract: SAR images are different from optical images in many ways. Therefore, the traditional compression methods, which have been used for compression, are not so efficient for the compression of the SAR images. Generally, 2-dimensional Fourier transform (2D-FT) is used for representing a complex SAR image. But, the energy of the coefficients of 2D-FT on the complex SAR image distributes in the whole frequency domain also. Typically, the frequency signals are divided into two parts, i.e., real and imaginary parts. A Wavelet transform gives very strong de correlation ability and can be used for local analysis in time and frequency with different scales. Wavelet transform have also been applied to complex SAR image compression, as it is suitable for non-stationary signal processing. We have embodied the wavelet transform with SPIHT for compression of SAR images. Also FFT is used for converting the complex SAR image into a real image before applying it to DWT. In particular, we have used Le Gall 5/3 biorthogonal wavelet for calculating the wavelet transform.

Keywords: Discrete Wavelet Transform (DWT), Fast Fourier Transform (FFT), Synthetic Aperture Radar (SAR), SPIHT, Image Compression, PSNR.