Still Image Compression Coding Based On Adaptive Wavelet Transform

Wavelet transform is a useful mathematical tool for most signal and image processing. The second generation wavelet-lifting scheme makes wavelet theories more simple and versatile in use. Image coding and compression based on adaptive lifting scheme transform are researched in this thesis. The main contributions are as follows:Firstly, Wavelet transform and lifting scheme are studied; The criterion of choosing wavelet bases during coding is analyzed.Secondly, The schematic theory of image coding and compression via adaptive transforms is developed. The cost functions commonly used for adaptive transforms are summarized.Thirdly, Conventional lifting schemes are introduced and varieties of performances are analyzed. Combined with various applications in image coding and compression, lifting scheme transform is compared with wavelet transform in both hard realization and computation burden.Finally, Lossless compression by means of integer lifting scheme is realized. After selecting a practical bases of lifting scheme transform, we put forward to two lossy compression algorithms based on adaptive transform and demonstrate its feasibility and validity by simulation and experiment.