scholarly journals A FAST ENCODING FRACTAL IMAGE COMPRESSION USING QUANTIZED QUAD- TREE PARTITIONING TECHNIQUES

2021 ◽  
Vol 6 (1) ◽  
pp. 52-57
Author(s):  
Atish Khobragade ◽  
Ajay Meshram ◽  
Komal Meshram
Keyword(s):  
Image Compression ◽  
Fractal Image Compression ◽  
Fast Encoding ◽  
Fractal Image ◽  
Quad Tree

scholarly journals A fast encoding algorithm for fractal image compression

2004 ◽  
Vol 1 (12) ◽  
pp. 352-357
Author(s):  
Chou-Chen Wang ◽  
Jung-Yang Kao
Keyword(s):  
Image Compression ◽  
Fractal Image Compression ◽  
Fast Encoding ◽  
Fractal Image

Codebook Clustering by Self-Organizing Maps for Fractal Image Compression

Fractals ◽  
1997 ◽  
Vol 05 (supp01) ◽  
pp. 27-38 ◽  
Author(s):  
Raouf Hamzaoui
Keyword(s):  
Image Compression ◽  
Clustering Algorithm ◽  
Not Given ◽  
Fractal Image Compression ◽  
Self Organizing Maps ◽  
Classification Schemes ◽  
Fast Encoding ◽  
Fractal Image ◽  
Traditional Classification ◽  
Self Organizing

A fast encoding scheme for fractal image compression is presented. The method uses a clustering algorithm based on Kohonen's self-organizing maps. Domain blocks are clustered, yielding a classification with a notion of distance which is not given in traditional classification schemes.

A fast encoding algorithm for fractal image compression using the DCT inner product

2000 ◽  
Vol 9 (4) ◽  
pp. 529-535 ◽  
Author(s):  
Trieu-Kien Truong ◽  
Jyh-Horng Jeng ◽  
I.S. Reed ◽  
P.C. Lee ◽  
A.Q. Li
Keyword(s):  
Image Compression ◽  
Inner Product ◽  
Fractal Image Compression ◽  
Fast Encoding ◽  
Fractal Image

FRACTAL IMAGE COMPRESSION USING LOCALLY REFINED PARTITIONS

Fractals ◽  
1994 ◽  
Vol 02 (03) ◽  
pp. 405-408
Author(s):  
D. CAI ◽  
T. ARISAWA ◽  
N. ASAI ◽  
Y. IKEBE ◽  
T. ITOH
Keyword(s):  
Image Compression ◽  
Present Report ◽  
Compression Method ◽  
File Size ◽  
Fractal Image Compression ◽  
Fractal Image ◽  
Quad Tree

In the present report, we show a practical fractal image compression method using locally refined partition which is generated automatically and controlled by the values of gradients in images, The method is similar to the ones by Barnsley and Hurd. In our method, using the quad-tree scheme, before the compression processes of the image, we locally refine the domain regions recursively until the size of the regions become smaller than the scale lengths of the gradients in the image or until the predefined minimum refinement size is reached. Based on our method, it is possible to assess the optimum-like set of domain regions for the desired file size.

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