Comparison of image compression techniques using huffman coding, DWT and fractal algorithm

Image compression is one of the advantageous techniques in different types of multi-media services. Image Compression technique have been emerged as one of the most important and successful applications in image analysis. In this paper the proposal of image compression using simple coding techniques called Huffman; Discrete Wavelet Transform (DWT) coding and fractal algorithm is done. These techniques are simple in implementation and utilize less memory. Huffman coding technique involves in reducing the redundant data in input images. DWT can be able to improve the quality of compressed image. Fractal algorithm involves encoding process and gives better compression ratio. By using the above algorithms the calculation of Peak signal to noise ratio (PSNR), Mean Square error (MSE) and compression ratio (CR) and Bits per pixel (BPP) of the compressed image by giving 512×512 input images and also the comparison of performance analysis of the parameters with that above algorithms is done. The result clearly explains that Fractal algorithm provides better Compression ratio (CR) and Peak Signal to noise ratio (PSNR).