scholarly journals Nouvelle approche d’accélération du codage fractal d’images

2009 ◽  
Vol Volume 11, 2009 - Special... ◽  
Author(s):  
Sofia Douda ◽  
Abdelhakim El Imrani ◽  
Mohammed Limouri
Keyword(s):  
Computational Complexity ◽  
Image Quality ◽  
Compression Ratio ◽  
Classification Methods ◽  
Fractal Image Compression ◽  
Fractal Image ◽  
Fast Decoding ◽  
Reduction Methods ◽  
Speed Up ◽  
International Audience

International audience The Fractal image compression has the advantage of presenting fast decoding and independent resolution but it suffers of slow encoding phase. In the present study, we propose to reduce the computational complexity by using two domain pools instead of one domain pool and encoding an image in two steps (AP2D approach). AP2D could be applied to classification methods or domain pool reduction methods leading to more reduction in encoding phase. Indeed, experimental results showed that AP2D speed up the encoding time. The time reduction obtained reached a percentage of more than 65% when AP2D was applied to Fisher classification and more than 72% when AP2D was applied to exhaustive search. The image quality was not altered by this approach while the compression ratio was slightly enhanced. La compression fractale d’images permet un décodage rapide et une indépendance de la résolution mais souffre d’une lenteur dans le codage. Le présent travail présente une approche visant à réduire le temps de calcul en utilisant deux dictionnaires et une approximation de l’image en deux étapes (AP2D). L’approche AP2D peut être appliquée aux méthodes de classification ou aux méthodes de réduction du cardinal du dictionnaire et ainsi réduire davantage le temps de codage. Les résultats expérimentaux ont montré que AP2D appliquée à une recherche exhaustive a atteint un gain de temps de plus de 72%. De même AP2D appliquée à la classification de Fisher a permis une réduction de temps de codage de plus de 65%. La qualité de l’image n’a pas été altérée par cette approche et le taux de compression a légèrement augmenté.

scholarly journals Fractal Image Compression Based on High Entropy Values Technique

2018 ◽  
Vol 28 (2) ◽  
pp. 119
Author(s):  
Douaa Younis Abbaas
Keyword(s):  
Image Quality ◽  
Compression Ratio ◽  
Search Algorithm ◽  
Fractal Image Compression ◽  
High Entropy ◽  
Fractal Image ◽  
Reconstruction Image ◽  
Domain Block ◽  
Entropy Technique ◽  
Full Search

There are many attempts tried to improve the encoding stage of FIC because it consumed time. These attempts worked by reducing size of the search pool for pair range-domain matching but most of them led to get a bad quality, or a lower compression ratio of reconstructed image. This paper aims to present a method to improve performance of the full search algorithm by combining FIC (lossy compression) and another lossless technique (in this case entropy coding is used). The entropy technique will reduce size of the domain pool (i. e., number of domain blocks) based on the entropy value of each range block and domain block and then comparing the results of full search algorithm and proposed algorithm based on entropy technique to see each of which give best results (such as reduced the encoding time with acceptable values in both compression quali-ty parameters which are C. R (Compression Ratio) and PSNR (Image Quality). The experimental results of the proposed algorithm proven that using the proposed entropy technique reduces the encoding time while keeping compression rates and reconstruction image quality good as soon as possible.

CRITICAL REVIEW OF FRACTAL IMAGE COMPRESSION

1995 ◽  
Vol 06 (01) ◽  
pp. 47-66 ◽  
Author(s):  
HARRI RAITTINEN ◽  
KIMMO KASKI
Keyword(s):  
Image Quality ◽  
Image Compression ◽  
Compression Ratio ◽  
Critical Review ◽  
Quality Measures ◽  
Fractal Image Compression ◽  
Fractal Compression ◽  
New Methods ◽  
Fractal Image ◽  
Image Quality Measures

In this paper, fractal compression methods are reviewed. Three new methods are developed and their results are compared with the results obtained using four previously published fractal compression methods. Furthermore, we have compared the results of these methods with the standard JPEG method. For comparison, we have used an extensive set of image quality measures. According to these tests, fractal methods do not yield significantly better compression results when compared with conventional methods. This is especially the case when high coding accuracy (small compression ratio) is desired.

scholarly journals Merge Operation Effect On Image Compression Using Fractal Technique

2007 ◽  
Vol 4 (1) ◽  
pp. 169-173
Author(s):  
Baghdad Science Journal
Keyword(s):  
Image Compression ◽  
Rate Distortion ◽  
Experimental Results ◽  
Fractal Image Compression ◽  
Fractal Image ◽  
Statistical Measures ◽  
Fast Decoding

Fractal image compression gives some desirable properties like fast decoding image, and very good rate-distortion curves, but suffers from a high encoding time. In fractal image compression a partitioning of the image into ranges is required. In this work, we introduced good partitioning process by means of merge approach, since some ranges are connected to the others. This paper presents a method to reduce the encoding time of this technique by reducing the number of range blocks based on the computing the statistical measures between them . Experimental results on standard images show that the proposed method yields minimize (decrease) the encoding time and remain the quality results passable visually.

scholarly journals Improving Fractal Image Compression Scheme through Quantization Operation

2007 ◽  
Vol 4 (2) ◽  
pp. 330-337
Author(s):  
Baghdad Science Journal
Keyword(s):  
Image Quality ◽  
Image Compression ◽  
New Method ◽  
Compression Scheme ◽  
Fractal Image Compression ◽  
High Image Quality ◽  
Fractal Image ◽  
Separate Step ◽  
Transform Coefficients

We explore the transform coefficients of fractal and exploit new method to improve the compression capabilities of these schemes. In most of the standard encoder/ decoder systems the quantization/ de-quantization managed as a separate step, here we introduce new way (method) to work (managed) simultaneously. Additional compression is achieved by this method with high image quality as you will see later.

IMPROVED FRACTAL IMAGE COMPRESSION BASED ON ROBUST FEATURE DESCRIPTORS

2011 ◽  
Vol 11 (04) ◽  
pp. 571-587 ◽  
Author(s):  
WILLIAM ROBSON SCHWARTZ ◽  
HELIO PEDRINI
Keyword(s):  
Image Compression ◽  
Computational Cost ◽  
Computational Time ◽  
Natural Scenes ◽  
Fractal Image Compression ◽  
Fractal Image ◽  
Feature Descriptors ◽  
High Compression ◽  
Speed Up ◽  
Computationally Intensive

Fractal image compression is one of the most promising techniques for image compression due to advantages such as resolution independence and fast decompression. It exploits the fact that natural scenes present self-similarity to remove redundancy and obtain high compression rates with smaller quality degradation compared to traditional compression methods. The main drawback of fractal compression is its computationally intensive encoding process, due to the need for searching regions with high similarity in the image. Several approaches have been developed to reduce the computational cost to locate similar regions. In this work, we propose a method based on robust feature descriptors to speed up the encoding time. The use of robust features provides more discriminative and representative information for regions of the image. When the regions are better represented, the search for similar parts of the image can be reduced to focus only on the most likely matching candidates, which leads to reduction on the computational time. Our experimental results show that the use of robust feature descriptors reduces the encoding time while keeping high compression rates and reconstruction quality.

scholarly journals A NOVEL FAST FRACTAL IMAGE COMPRESSION METHOD BASED ON DISTANCE CLUSTERING IN HIGH DIMENSIONAL SPHERE SURFACE

Fractals ◽  
2017 ◽  
Vol 25 (04) ◽  
pp. 1740004 ◽  
Author(s):  
SHUAI LIU ◽  
ZHENG PAN ◽  
XIAOCHUN CHENG
Keyword(s):  
Image Compression ◽  
High Dimensional ◽  
Dimensional Sphere ◽  
Compression Method ◽  
Sphere Surface ◽  
Fractal Image Compression ◽  
Fractal Compression ◽  
Fractal Image ◽  
Speed Up ◽  
Encoding Method

Fractal encoding method becomes an effective image compression method because of its high compression ratio and short decompressing time. But one problem of known fractal compression method is its high computational complexity and consequent long compressing time. To address this issue, in this paper, distance clustering in high dimensional sphere surface is applied to speed up the fractal compression method. Firstly, as a preprocessing strategy, an image is divided into blocks, which are mapped on high dimensional sphere surface. Secondly, a novel image matching method is presented based on distance clustering on high dimensional sphere surface. Then, the correctness and effectiveness properties of the mentioned method are analyzed. Finally, experimental results validate the positive performance gain of the method.

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