scholarly journals Design of Faster Fractal Image Compression using Intensity Mismatch Threshold

2019 ◽  
Vol 9 (1) ◽  
pp. 2097-2100
Keyword(s):  
Image Compression ◽  
Hardware Implementation ◽  
Fractal Image Compression ◽  
Major Drawback ◽  
Fractal Image ◽  
Block Form ◽  
The Mean ◽  
Domain Block ◽  
Mean Time ◽  
Similar Domain

Within the domain of image processing the applications of the fractal image compression through the affine transform is rarely implemented. The major drawback it consists is its time consumptions in simulations as well as in hardware implementation. The reason behind this is its comparatively matching the range blocks with the varied number of domain blocks. Additionally, the compression ration obtained from this sets of techniques are much more that the other similar working techniques. In order to overcome, this drawback, here a concept of intensity mismatch searching techniques is intruded within this particular paper. While in the mean time, it only concluded in much reduce in time of searching for similar domain block form a pool. And also this technique does not affect within the compression ratio and PSNR measurement form the retrieved image. Further benefitted in hardware applications where the matters for time consumptions is a major factor.

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.

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.

Efficient Domain Search for Fractal Image Compression Using Feature Extraction Technique

2012 ◽  
Vol 488-489 ◽  
pp. 1587-1591
Author(s):  
Amol G. Baviskar ◽  
S. S. Pawale
Keyword(s):  
Feature Extraction ◽  
Image Compression ◽  
Low Complexity ◽  
Contractive Mapping ◽  
Fractal Image Compression ◽  
Compression Technique ◽  
Image Encoding ◽  
Fractal Image ◽  
Coding Method ◽  
The Given

Fractal image compression is a lossy compression technique developed in the early 1990s. It makes use of the local self-similarity property existing in an image and finds a contractive mapping affine transformation (fractal transform) T, such that the fixed point of T is close to the given image in a suitable metric. It has generated much interest due to its promise of high compression ratios with good decompression quality. Image encoding based on fractal block-coding method relies on assumption that image redundancy can be efficiently exploited through block-self transformability. It has shown promise in producing high fidelity, resolution independent images. The low complexity of decoding process also suggested use in real time applications. The high encoding time, in combination with patents on technology have unfortunately discouraged results. In this paper, we have proposed efficient domain search technique using feature extraction for the encoding of fractal image which reduces encoding-decoding time and proposed technique improves quality of compressed image.

Sign in / Sign up

Export Citation Format

Share Document