Texture mapping has traditionally been used to add visual realism to computer graphics images. In the paper we propose an alternative technique for image texture handling. We use fractal image compression scheme to compress and decompress large and complex textures. We identify special properties of the method to apply in the very process of texture mapping. The main idea is to exploit high degree of local self-similarity in natural textures. The method allows for very high compression of complex textures, provides real-time decompression and perfectly suits Level of Detail. Properties of the method are compared to those of classical DCT and wavelet compression schemes
In this thesis we present an overview of image processing techniques which use fractal methods in so...
An efficient texture compression method is proposed based on a block matching process between the cu...
A deterministic fractal is an image which has low information content and no inherent scale. Because...
Texture mapping has traditionally been used to add visual realism to computer graphics images. In th...
Abstract: Texture mapping has traditionally added visual realism to computer graphics images. Modern...
Digital image processing is exploited in many diverse applications but the size of digital images pl...
With the rapid increase in the use of computers and internet, the demand for higher transmission and...
The objectives in the first part are to obtain large compression ratio and high image quality after ...
this article, we will explore a new scheme based on fractals. Such a scheme has been promoted by M. ...
The technique of Fractal Image Compression, although new, has been described in several ways. Thus f...
FIC Fractal Image Processing is actually a JPG image which needs to be perform large scale encoding ...
The article considered application of the method of compression mappings and the method of successiv...
With the rapid increase in the use of computers and internet, the demand for higher transmission and...
Fractal compression is a loss compression method for digital images, based on fractals. The method i...
In the present work we study fractal image compression. We discuss basic techniques, published impro...
In this thesis we present an overview of image processing techniques which use fractal methods in so...
An efficient texture compression method is proposed based on a block matching process between the cu...
A deterministic fractal is an image which has low information content and no inherent scale. Because...
Texture mapping has traditionally been used to add visual realism to computer graphics images. In th...
Abstract: Texture mapping has traditionally added visual realism to computer graphics images. Modern...
Digital image processing is exploited in many diverse applications but the size of digital images pl...
With the rapid increase in the use of computers and internet, the demand for higher transmission and...
The objectives in the first part are to obtain large compression ratio and high image quality after ...
this article, we will explore a new scheme based on fractals. Such a scheme has been promoted by M. ...
The technique of Fractal Image Compression, although new, has been described in several ways. Thus f...
FIC Fractal Image Processing is actually a JPG image which needs to be perform large scale encoding ...
The article considered application of the method of compression mappings and the method of successiv...
With the rapid increase in the use of computers and internet, the demand for higher transmission and...
Fractal compression is a loss compression method for digital images, based on fractals. The method i...
In the present work we study fractal image compression. We discuss basic techniques, published impro...
In this thesis we present an overview of image processing techniques which use fractal methods in so...
An efficient texture compression method is proposed based on a block matching process between the cu...
A deterministic fractal is an image which has low information content and no inherent scale. Because...