A new image compression scheme using hyperanalytic wavelet transform and SPIHT

2013 ◽  
Vol 6 ◽  
pp. 87-98
Author(s):  
D. Prathyusha Reddi ◽  
M. N. Giri Prasad ◽  
S. Varadarajan
Keyword(s):  
Wavelet Transform ◽  
Image Compression ◽  
Compression Scheme

Merging Fractal Image Compression and Wavelet Transform Methods

Fractals ◽  
1997 ◽  
Vol 05 (supp01) ◽  
pp. 3-15 ◽  
Author(s):  
A. van de Walle
Keyword(s):  
Wavelet Transform ◽  
Image Compression ◽  
Iterated Function System ◽  
Wavelet Coefficients ◽  
Convergence Criteria ◽  
Compression Scheme ◽  
Fractal Image Compression ◽  
Transform Methods ◽  
Fractal Image ◽  
Wavelet Space

Fractal image compression and wavelet transform methods can be combined into a single compression scheme by using an iterated function system to generate the wavelet coefficients. The main advantage of this approach is to significantly reduce the tiling artifacts: operating in wavelet space allows range blocks to overlap without introducing redundant coding. Our scheme also permits reconstruction in a finite number of iterations and lets us relax convergence criteria. Moreover, wavelet coefficients provide a natural and efficient way to classify domain blocks in order to shorten compression times. Conventional fractal compression can be seen as a particular case of our general algorithm if we choose the Haar wavelet decomposition. On the other hand, our algorithm gradually reduces to conventional wavelet compression techniques as more and more range blocks fail to be properly approximated by rescaled domain blocks.

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