반복 수축 변환을 이용한 프랙탈 영상압축

Fractal Image Compression using the Iterated Contractive Transformation

In this paper an image compression technique based on fractal theory using iterated contractive transformation is analysed and an improved image coder is suggested. Existing methods used the classifier proposed by Ramamurthi and Gersho which utilize the properties of neighboring pixels in the spatial domain. In this paper DCT-based classification is applied to 512$\times$512 images and PSNR improvement of 0.4~2.7 dB is obtained at lower bit rate over conventional algorithms. In addition the effect of varying the domain block size and quantization step size of the luminance shift parameter on the compression ratio and the image quality is compared and analysed.