The need for compression is to minimize the storage space and reduction of transmission cost. When a digital image is transmitted through a communication channel, the cost of the transmission depends on the size of the data. The only way currently to improve on these resource requirements is to compress images such that they can be transmitted quicker and then decompressed by the receiver. There are many applications requiring image compression such as multimedia, internet, satellite imaging, remote sensing, preservation of art work, etc. Numerous methods for image compression have been presented in the literature survey but there is always a scope for improvement. In current work the fractal image compression has been employed as an efficient method in image compression. A novel compression encoding technique using hard threshold has been proposed based on fractal image compression and the results are compared with the other state of art image compression methods. The proposed method reduces the Encoding time significantly while some what compromising with the quality of the image. The initial experiments show that the proposed approach could achieve smaller encoding time and higher compression ratio on images. The proposed algorithm exhibits promising results from quantitatively and qualitatively points of view.

Compression Contractive transform Fractal Iterative Function System Thresholding