Generally the fractal image compression is a technique based on the presentation of an image by a contractive transform, on the space of image, for which the fixed point is close to the original image. The fractal image compression is rapidly growing principle covers a wide variety of coding scheme in various domains. A large number of theoretical aspects of this concept are available. However,...

This resembles a fractal transform, and the coefficient values can be calculated using a least squares fit as done by Monro [3] for fractals. The major difference from fractals is that the block(x,y) values are predetermined, and therefore to render the image there is no need for the iteration associated with fractals. The RIBs are effectively the difference between the polynomial coded image a...

Decoding a fractal compressed image can be seen as solving an aane two-scale functional equation. If the aane term is zero, the dilation equation becomes linear and the solution is similar to the scaling functions from wavelet theory. In both cases a linear operator, parameter-ized with a few variables determines a complicate looking function. We present two classes of algorithms for gray image...

Decoding a fractal compressed image can be seen as solving an a ne two-scale functional equation. If the a ne term is zero, the dilation equation becomes linear and the solution is similar to the scaling functions from wavelet theory. In both cases a linear operator, parameterized with a few variables determines a complicate looking function. We present two classes of algorithms for gray image ...

In this paper a new hardware method for fast and low power fractal coding is presented. The introduced method is based on binary classification of domain and range blocks. The technique not only reduces power consumption and increases processing speed but also has minimal effect on the degradation of the output result compared to the available fractal techniques. In order to show the functional...

This paper reports on investigations concerning the convergence of fractal transforms for signal modelling. Convergence is essential for the functionality of fractal based coding schemes. The coding process is described as non-linear transformation in the finite-dimensional vector space. Using spectral theory, a necessary and sufficient condition for the contractivity is derived from the eigenv...

We present a novel method of image expansion using vector quantisation. The algorithm is inspired by fractal coding and uses a statistical model of the relationship between details at different scales of the image to interpolate detail at one octave above the highest spatial frequency in the original image. Our method aims at overcoming the drawbacks associated with traditional approaches such ...

This paper presents a method for fast encoding of still images based on iterated function systems (IFSs). The major disadvantage of this coding approach, usually referred to as fractal coding, is the high computational effort of the encoding process compared to e.g. the JPEG algorithm [1]. This is mainly due to the costly “full search” of the transform parameters within a fractal codebook. We t...

Digital image databases represent huge amount of data, automatic indexing and content base retrieval are crucial factors. IFS ( Iterated function system ) fractal code can be used to retrieve image and the position parameter of IFS code is replaced with the relative distance and direction parameter. A new algorithm of IFS fractal code for image retrieval on compression domain is presented in th...