Research On Image Compression Using Multi-Wavelet And Time-Frequency Lapped Transform

Nowadays compression method based upon wavelet transform has become the mainstream in image compressing field. But as we all know, wavelet transform can't satisfy the requirement of portable devices and Space-Based compression for its drawback in large storing cost and high calculating complexity. Fortunately, Lapped Transform(LT), a classical transform arithmetic, possesses the DCT's feature of simple realization and low storing cost, while maintaining DWT's advantage. By analyzing its Time Lapped Transform(TLT) and Frequency Lapped Transform (FLT), this article brings forward a arithmetic which carries the temporal laps and frequent laps at the same time and discusses this time-frequency lapped method(TFLT) combining with context-based entropy coding. Experimental results implicate that this arithmetic is a low storage-cost and complicated method, for its better performance over JPEG2000 in both realization and storage requirement.Owing to combination of smoothness, tight support, symmetry, orthogonality and higher order of vanish moments, Multi-wavelets supply us with a new signal analysis method , which can better approximate the signal and performance well on the edge in reconstruction. Combining the favorable capability of EBCOT and characteristic of Multi-wavelet's coefficients, This article puts forward an integrated filter and pretreatment method based on approximated stairs. It processes the vector quantification of Multi-wavelet's coefficients and carries out the mix-scan compression arithmetic towards bit planes of EBCOT. Experimental results show that this method reduces calculating complexity to some extent while obtaining favorable compressing effects.