Title :
Low complexity fractal-based image compression technique
Author :
Kumar, Sunil ; Jain, R.C.
Author_Institution :
Electr. & Electron. Eng. Dept., Birla Inst. of Technol., Pilani, India
fDate :
11/1/1997 12:00:00 AM
Abstract :
A fast image compression technique as well as its progressive image transmission (PIT) version using fractals is presented which uses a small pool of domains extracted using visually significant patterns. The affine transformations for an edge block are obtained by using its edge characteristics instead of the minimum mean square error criterion. Simulation studies demonstrate that this method is computationally simple, gives faster encoding speed and achieves good fidelity at relatively higher compression ratios than other fractal based techniques
Keywords :
computational complexity; data compression; edge detection; feature extraction; fractals; image coding; transform coding; transforms; visual communication; PIT; affine transformations; compression ratios; consumer entertainment; edge block; edge characteristics; encoding speed; fidelity; fractals; low complexity fractal-based image compression technique; progressive image transmission; visually significant patterns; Bandwidth; Broadcasting; Computational modeling; Discrete cosine transforms; Fractals; Image coding; Image communication; Mean square error methods; Vector quantization; Video compression;
Journal_Title :
Consumer Electronics, IEEE Transactions on