A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
The JPEG still picture compression standard
Communications of the ACM - Special issue on digital multimedia systems
Fractal image compression
Ten lectures on wavelets
Fractal image compression: theory and application
Fractal image compression: theory and application
JPEG Still Image Data Compression Standard
JPEG Still Image Data Compression Standard
IEEE Transactions on Computers
On the performance of fractal compression with clustering
IEEE Transactions on Image Processing
A new, fast, and efficient image codec based on set partitioning in hierarchical trees
IEEE Transactions on Circuits and Systems for Video Technology
Computer Methods and Programs in Biomedicine
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This paper attempts to give a recipe for selecting one of the popular image compression algorithms based on (a) Wavelet, (b) JPEG/DCT, (c) VQ, and (d) Fractal approaches. We review and discuss the advantages and disadvantages of these algorithms for compressing grayscale images, give an experimental comparison on four 256脳256 commonly used images, Jet, Lenna, Mandrill, Peppers, and one 400脳400 fingerprint image. Our experiments show that all of the four approaches perform satisfactorily when the 0.5 bits per pixel (bpp) is desired. However, for a low bit rate compression like 0.25 bpp or lower, the embedded zerotree wavelet (EZW) approach and DCT-based JPEG approach are more practical.