Today, in the multimedia encoding technology, fractal image coding is an effective coding method without resolution. The effectiveness is because of the high compressing ratio of fractal image coding. But the computational complexity of this coding method is so high that it needs long encoding time. In this paper, a novel fast fractal coding method is constructed to decrease the coding time by ...

Fractal image coding can be seen as spectral prediction of coefficients in the wavelet decomposition of an image. Fine scale coefficients are described by shifted and scaled coefficients from the next coarser frequency scale. We analyzed the ability of fractal coders to predict wavelet coefficients and found that the prediction of entire wavelet subtrees-as done by conventional spatial domain f...

The author proposes an independent and novel approach to image coding, based on a fractal theory of iterated transformations. The main characteristics of this approach are that (i) it relies on the assumption that image redundancy can be efficiently exploited through self-transformability on a block-wise basis, and (ii) it approximates an original image by a fractal image. The author refers to ...

Fractal coding suffered from low coding efficiency, difficulties to obtain high quality encoding of images, and blocking artifacts at low bit rates and exhaustive inherent coding time. Blocking artifacts can be avoided if fractal coding is performed in the wavelet domain. A new fast and efficient image coder is developed that applies the speed of the wavelet transform to the image quality of th...

In fractal compression a signal is encoded by the parameters of a contractive transformation whose fixed point (attractor) is an approximation of the original data. Thus fractal coding can be viewed as the optimization problem of finding in a set of admissible contractive transformations the transformation whose attractor is closest to a given signal. The standard fractal coding scheme based on...

This work results from a fractal image compression based on iterated transforms and machine learning modeling. In this work an improved quasi-losses fractal coding scheme is addressed to preserve the rich features of the medical image as the domain blocks and to generate the remaining part of the image from it based on fractal transformations. Machine learning based model is used for improving ...

Progressive coding is an important feature of compression schemes. Wavelet coders are well suited for this purpose because the wavelet coefficients can be naturally ordered according to decreasing importance. Progressive fractal coding is feasible, but it was proposed only for hybrid fractal-wavelet schemes. We introduce a progressive fractal image coder in the spatial domain. A Lagrange optimi...

In this paper, fractal monochrome image compression technique proposed by Jacquin is investigated for 24-bit true color image by encoding the RGB components' images independently. To exploit the spectral redundancy in RGB components, the root mean square error distortion measure in grayscale space is extended to 3-dimensional color space for fractal-based color image coding. Experimental result...

The main purpose of image compression is to use as many bits as possible to represent the source image by eliminating the image redundancy with acceptable restoration. Fractal image compression coding has achieved good results in the field of image compression due to its high compression ratio, fast decoding speed as well as independency between decoding image and resolution. However, there is ...

-Fractal image coding has become a popular research area for the past decade, it has been widely used for commercial purpose. The major problem of fractal image coding is the excessive long encoding time. In this paper, we propose an VLSI design for speeding up of fractal image encoding. Simulation results show that the design is quite efficient.