A novel hybrid bi-orthogonal wavelets/ADPCM algorithm for very low bit rate satellite image compression

Abstract

n this paper, we present an overview of image compression using wavelet transforms. We begin by describing the wavelet properties that are most important for image compression. In particular, we present a method to construct bi-orthogonal wavelets and their Finite €mpulse Response (FIR) filter banks. All of these FIR filter banks all have linear phase characteristics and the signa€ can be many high frequency details, such as building structures igation. Using our hyttrid algorithm, the data was maintained w i b a Peak Signal-to-PWse Ratio (PSNR) of approximahly 26dB while achieving a compression ratio of 150:l. NTRODUCTIONDue to the vast mount of digital images associated with satellite remote sensing, image compression has became a key technology for &e transmission and storage of satellite images. In the past ten years, the spatial and resolutions of satetlite remote sensing have significantly. The w e d for more efficient data c the remote sensing community. numerous applications in speech and image processing. But the blocking effects of VQ have restricted the application of VQ codes in satellite image compression.The tppic of "wavelet analysis" has recently atmsted much attention from both mathematicians and engineers. Wavelet theory has found applications in areas such as image analysis, communication systems, biomedical imaging, radar, ~