Fractal image compression of Satellite imageries using variable size of range block

Fractal image compressions of Standard Lena and Satellite imageries have been carried out for the variable size range block method. The image is partitioned by considering maximum and minimum size of the range block and matching it with the domain block. The domain block size of window K*K are sliding over the entire image in steps of K/2. Affine transformation and entropy coding are applied to achieve fractal compression. The Matlab simulation for the standard Lena, and Satellite imageries have been carried out for three different cases of variable range block sizes. The image is reconstructed using iterative functions and inverse transforms. The results of the fractal compression scheme indicate that for the case R
max
= 16 and R
min
= 8, it is possible to achieve higher Compression Ratio (CR) ∼ 16 and good Peak Signal to Noise Ratios (PSNR) ∼21 dB for satellite imageries. The fractal compression scheme with variable range methods are found to be better than the fixed range methods for achieving higher compression ratios and PSNR values for satellite imageries. The results are presented and discussed in the paper.