An Adaptive Partition for Fractal Image Coding

Fractals ◽  
1997 ◽  
Vol 05 (supp01) ◽  
pp. 243-256 ◽  
Author(s):  
Franck Davoine ◽  
Etienne Bertin ◽  
Jean-Marc Chassery
Keyword(s):  
Compression Ratio ◽  
Image Coding ◽  
Visual Quality ◽  
Second Step ◽  
Affine Transformations ◽  
Fractal Image Compression ◽  
Fractal Image ◽  
Fractal Image Coding ◽  
Delaunay Triangles

In this paper we present a flexible partitioning scheme for fractal image compression, based on the Delaunay triangles. The aim is to have the advantage of triangular blocks over squares, in terms of adaptivity to the image content. In a first step, the triangulation is computed so that the triangles are more densely distributed in regions containing interesting features such as corners and edges, or so that they tend to run along the strong edges in the image. In a second step we merge adjacent triangles into quadrilaterals, in order to decrease the number of blocks. Quadrilaterals permit a reduction of the number of local contractive affine transformations composing the fractal transform, and thus to increase the compression ratio, while preserving the visual quality of the decoded image.

Improvement of Fractal Image Compression Coding Based on Quadtree

2012 ◽  
Vol 532-533 ◽  
pp. 1157-1161
Author(s):  
Hong Tao Hu ◽  
Qi Fei Liu
Keyword(s):  
Image Compression ◽  
Image Coding ◽  
Original Image ◽  
Fractal Image Compression ◽  
Fractal Image ◽  
Fractal Image Coding ◽  
Global Matching ◽  
Domain Block ◽  
Compression Coding

The goal of image compression is to represent an image with as few number of bits as possible while keeping the quality of the original image. With the characteristics of higher compression ratio, fractal image coding has received much attention recently. However, conventional fractal compression approach needs more time to code the original image. In order to overcome the time-consuming issue, a Quadtree-based partitioning and matching scheme is proposed. During the partitioning phase, an image frame is partitioned into tree-structural segments. And during a matching phase, a rang block only searches its corresponding domain block around previous matched domain block. Such local matching procedures will not stop until a predefined matching threshold is obtained. The preliminary experimental results show that such sub-matching rather than a global matching scheme dramatically decreases the matching complexity, while preserving the quality of an approximate image to the original after decoding process. In particular, the proposed scheme improves the coding process up to 2 times against the conventional fractal image coding approach.

Modified No Search Scheme based Domain Blocks Sorting Strategies for Fractal Image Coding

2014 ◽  
Vol 69 (10-11) ◽  
pp. 511-520
Author(s):  
Xing-Yuan Wang ◽  
Dou-Dou Zhang ◽  
Na Wei
Keyword(s):  
Mean Square Error ◽  
Image Coding ◽  
The Other ◽  
Mean Square ◽  
Minimum Value ◽  
Fractal Image ◽  
Fractal Image Coding ◽  
Domain Block ◽  
Partition Method

AbstractA novel fractal image coding algorithm based on domain blocks sorting strategies and modified no search scheme is proposed in this paper. On one hand, in order to improve the encoding time, a modified no search (MNS) scheme is adopted. Firstly, the image is divided into blocks of different size utilizing an adaptive quadtree partition method. Secondly, one finds the location of the best matching domain block using the MNS scheme for the range blocks, whose sizes are larger than the preset minimum value. Thirdly, the types of the range block and domain block are computed employing the proposed approach, and then the corresponding computation of mean square error (MSE) is determined. The computation of the MSE is reduced and the encoding phase speeds up. On the other hand, the range blocks with the minimal sizes are encoded applying the proposed domain blocks sorting (DBS) method. Contrast experiment results show that the proposed algorithm can obtain good quality of the reconstructed images and shorten the encoding time significantly.

scholarly journals Fractal Image Coding for Improve the Quality of Medical Images

2014 ◽  
Vol 8 (1) ◽  
pp. 19-26 ◽  
Author(s):  
Jaehong Park ◽  
Cheolwoo Park ◽  
Wonseok Yang
Keyword(s):  
Image Coding ◽  
Medical Images ◽  
Fractal Image ◽  
Fractal Image Coding

AN IMPROVED FRACTAL IMAGE CODING METHOD

Fractals ◽  
2009 ◽  
Vol 17 (04) ◽  
pp. 451-457 ◽  
Author(s):  
XING-YUAN WANG ◽  
FAN-PING LI ◽  
ZHI-FENG CHEN
Keyword(s):  
Image Coding ◽  
Nearest Neighbor ◽  
Optimal Solution ◽  
Search Method ◽  
Neighbor Search ◽  
Fractal Image ◽  
Fractal Image Coding ◽  
Coding Method ◽  
Domain Block

This paper presents a fast fractal image coding method based on quadtree division, improved neighbor search and asymptotic strategy. We search the optimal matched domain block of a range block in its five nearest neighbor blocks and make asymptotic moves along the direction of potential optimal solution. If the optimal solution can not be improved, we carry out quadtree division for this range block until it caters to our demand or reaches greatest division level. The experimental results show that the coding speed of the proposed method declined slightly, but it has a better quality of reconstructed image and higher compression ratio in comparisons with no search method.

scholarly journals Prediction of the PSNR Quality of Decoded Images in Fractal Image Coding

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Qiang Wang ◽  
Sheng Bi
Keyword(s):  
Computational Complexity ◽  
Curve Fitting ◽  
Image Coding ◽  
Prediction Method ◽  
Small Range ◽  
Fractal Coding ◽  
Fractal Image ◽  
Fractal Image Coding ◽  
Logarithmic Relationship

With many observations, we find that there exists a logarithmic relationship between the average collage error (ACER) and the PSNR quality of decoded images. By making use of ACER in the encoding process, the curve fitting result can help us to predict the PSNR quality of decoded images. Then, in order to reduce the computational complexity further, an accelerated version of the prediction method is proposed. Firstly, a low limit of percentage of accumulated collage error (LLPACE) is proposed to evaluate the actual percentage of accumulated collage error (APACE). If LLPACE reaches a large value, such as 90%, the corresponding APACE can be proved to be limited in a small range (90%–100%) and the APACE can be estimated approximately. Thus, the remaining range blocks can be neglected and the corresponding computations can be saved. With the approximated APACE and the logarithmic relationship, the quality of decoded images can be predicted directly. Experiments show that, for four fractal coding methods, the quality of decoded images can be predicted accurately. Furthermore, the accelerated prediction method can provide competitive performance and reduce about one-third of total computations in the encoding process. Finally, the application of the proposed method is also discussed and analyzed.

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