scholarly journals A NEW APPROACH OF FRACTAL COMPRESSION USING COLOR IMAGE

2020 ◽  
Vol 6 (6) ◽  
pp. 74-71
Author(s):  
Indrani Dalui ◽  
SurajitGoon ◽  
Avisek Chatterjee
Keyword(s):  
Image Coding ◽  
Color Image ◽  
Spatial Association ◽  
Three Dimensional ◽  
Gray Scale ◽  
Fractal Image Compression ◽  
Average Characteristic ◽  
Fractal Compression ◽  
Fractal Image ◽  
Fractal Properties

Fractal image compression depends on self-similarity, where one segment of a image is like the other one segment of a similar picture. Fractal coding is constantly connected to grey level images. The simplest technique to encode a color image by gray- scale fractal image coding algorithm is to part the RGB color image into three Channels - red, green and blue, and compress them independently by regarding each color segment as a specific gray-scale image. The colorimetric association of RGB color pictures is examined through the calculation of the relationship essential of their three-dimensional histogram. For normal color images, as a typical conduct, the connection necessary is found to pursue a power law, with a non- integer exponent type of a given image. This conduct recognizes a fractal or multiscale self-comparable sharing of the colors contained, in average characteristic pictures. This finding of a conceivable fractal structure in the colorimetric association of regular images complement other fractal properties recently saw in their spatial association. Such fractal colorimetric properties might be useful to the characterization and demonstrating of natural images, and may add to advance in vision. The outcomes got demonstrate that the fractal-based compression for the color image fills in similarly with respect to the color image.

scholarly journals BASED ON RANGE AND DOMAIN FRACTAL IMAGE COMPRESSION OF SATELLITE IMAGERIES IMPROVED ALGORITHM FOR RESEARCH

2014 ◽  
pp. 71-74
Author(s):  
SAEMA ENJELA ◽  
A.G. ANANTH
Keyword(s):  
Image Compression ◽  
Image Coding ◽  
Fractal Image Compression ◽  
Compression Technique ◽  
Fractal Coding ◽  
Fractal Compression ◽  
Urban Image ◽  
Fractal Image ◽  
Domain Block ◽  
Improved Algorithm

Fractal coding is a novel method to compress images, which was proposed by Barnsley, and implemented by Jacquin. It offers many advantages. Fractal image coding has the advantage of higher compression ratio, but is a lossy compression scheme. The encoding procedure consists of dividing the image into range blocks and domain blocks and then it takes a range block and matches it with the domain block. The image is encoded by partitioning the domain block and using affine transformation to achieve fractal compression. The image is reconstructed using iterative functions and inverse transforms. However, the encoding time of traditional fractal compression technique is too long to achieve real-time image compression, so it cannot be widely used. Based on the theory of fractal image compression; this paper raised an improved algorithm form the aspect of image segmentation. In the present work the fractal coding techniques are applied for the compression of satellite imageries. The Peak Signal to Noise Ratio (PSNR) values are determined for images namely Satellite Rural image and Satellite Urban image. The Matlab simulation results for the reconstructed image shows that PSNR values achievable for Satellite Rural image ~33 and for Satellite urban image ~42.

ENCODING VIDEO SEQUENCES IN FRACTAL-BASED COMPRESSION

Fractals ◽  
2007 ◽  
Vol 15 (04) ◽  
pp. 365-378 ◽  
Author(s):  
B. SANKARAGOMATHI ◽  
L. GANESAN ◽  
S. ARUMUGAM
Keyword(s):  
Image Compression ◽  
Motion Estimation ◽  
Color Image ◽  
Image Sequence ◽  
Color Images ◽  
Block Matching ◽  
Gray Scale ◽  
Fractal Image Compression ◽  
Estimation Algorithms ◽  
Fractal Image

With the rapid increase in the use of computers and the Internet, the demand for higher transmission and better storage is increasing as well. This paper describes the different techniques for data (image-video) compression in general and, in particular, the new compression technique called fractal image compression. Fractal image compression is based on self-similarity, where one part of an image is similar to the other part of the same image. Low bit rate color image sequence coding is very important for video transmission and storage applications. The most significant aspect of this work is the development of color images using fractal-based color image compression, since little work has been done previously in this area. The results obtained show that the fractal-based compression works for the color images works as well as for the gray-scale images. Nevertheless, the encoding of the color images takes more time than the gray-scale images. Color images are usually compressed in a luminance-chrominance coordinate space, with the compression performed independently for each coordinate by applying the monochrome image processing techniques. For image sequence compression, the design of an accurate and efficient algorithm for computing motion to exploit the temporal redundancy has been one of the most active research areas in computer vision and image compression. Pixel-based motion estimation algorithms address pixel correspondence directly by identifying a set of local features and computing a match between these features across the frames. These direct techniques share the common pitfall of high computation complexity resulting from the dense vector fields produced. For block matching motion estimation algorithms, the quad-tree data structure is frequently used in image coding to recursively decompose an image plane into four non-overlapping rectangular blocks.

Improved Algorithm of Fractal Compression Based on Average Deviation

2013 ◽  
Vol 475-476 ◽  
pp. 1001-1007
Author(s):  
Xiao Li Qin ◽  
Wei Luo ◽  
Yu Ping Li ◽  
Zheng Hui Xie ◽  
Lu Ye
Keyword(s):  
Image Coding ◽  
Block Matching ◽  
Search Range ◽  
Image Block ◽  
Fractal Image Compression ◽  
Average Deviation ◽  
Fractal Compression ◽  
Fractal Image ◽  
Domain Block ◽  
Improved Algorithm

Aiming at deficiency of fractal image compression, encoding time length and large amount of calculation, an improved algorithm of fractal compression is proposed based on the average deviation. First,divided image into blocks by using the characteristics of the average deviation, then determined the image block matching constraints by the application of the scale factor to simplify the calculation method, and finally limited the search range with the constraints, thus decrease the amount of the search range, improve the efficiency of the domain block matching. The simulation results show that the improved algorithm can reduce the computation of block matching, and improve the fractal image coding efficiency.

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.

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 Fractal Image Compression Using Canonical Huffman Coding

2020 ◽  
Vol 15 (1) ◽  
pp. 91-105
Author(s):  
Shree Ram Khaitu ◽  
Sanjeeb Prasad Panday
Keyword(s):  
Image Compression ◽  
Lossy Compression ◽  
Digital Data ◽  
Huffman Coding ◽  
Compression Scheme ◽  
Fractal Image Compression ◽  
Compression Technique ◽  
Fractal Compression ◽  
Fractal Image ◽  
Entropy Encoding

 Image Compression techniques have become a very important subject with the rapid growth of multimedia application. The main motivations behind the image compression are for the efficient and lossless transmission as well as for storage of digital data. Image Compression techniques are of two types; Lossless and Lossy compression techniques. Lossy compression techniques are applied for the natural images as minor loss of the data are acceptable. Entropy encoding is the lossless compression scheme that is independent with particular features of the media as it has its own unique codes and symbols. Huffman coding is an entropy coding approach for efficient transmission of data. This paper highlights the fractal image compression method based on the fractal features and searching and finding the best replacement blocks for the original image. Canonical Huffman coding which provides good fractal compression than arithmetic coding is used in this paper. The result obtained depicts that Canonical Huffman coding based fractal compression technique increases the speed of the compression and has better PNSR as well as better compression ratio than standard Huffman coding.  

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.

Face Detection Based on the Theory of Fractal Compression

2014 ◽  
Vol 945-949 ◽  
pp. 1825-1829
Author(s):  
Qing Sen An ◽  
Yue Bin Chen ◽  
Jing Fan ◽  
Jin Long Wang
Keyword(s):  
Image Compression ◽  
Face Detection ◽  
Iterated Function Systems ◽  
Fractal Image Compression ◽  
Fractal Compression ◽  
Fractal Image ◽  
Iterated Function ◽  
The Face ◽  
Face Similarity

The face detection has been a very important issue, the use of local and global face similarity between faces can be detected. In this paper, based on fractal image compression theory, we construct a local iterated function systems as a description of the face to detect the face.

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