A quadtree classified-based fractal image coding approach
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Abstract:
In this paper, an image coding approach is developed based on the quadtree classified method. It can solve the problem that some range blocks cannot be coded under the conventional fractal coding method. Experimental results show that compared to the conventional automatic fractal coding method, this approach can obtain high compression ratio with no apparent depression on the quality of the reconstructed image.Keywords:
Quadtree
Fractal transform
Fractal compression
In fractal image compression, quadtree image partitions are commonly used. The authors show that the error-based splitting criterion for nodes in the quadtree image partition can be replaced by a test based on block variances. This simplifies and speeds up the algorithm for fractal image compression without harming the rate-distortion performance of the encoder.
Quadtree
Fractal compression
Fractal transform
Data compression ratio
Distortion (music)
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Data compression as it is applicable to image processing is addressed. The relative effectiveness of several image compression strategies is analyzed. This study covers data compression algorithms, file format schemes, and fractal image compression. An overview of the popular LZW compression algorithm and its subsequent variations is also given. Several common image file formats are surveyed, highlighting the differing approaches to image compression. Fractal compression is examined in depth to reveal how an interactive approach to image compression is implemented. The performance of these techniques is compared for a variety of landscape images, considering such parameters as data reduction ratios and information loss.
Fractal compression
Texture compression
Fractal transform
Lossy compression
Data compression ratio
Color Cell Compression
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The compression time of fractal coding algorithm is so long that the algorithm is hardly useful in reality. The idea to preprocess the image by means of many grey levels was presented. It constructs a data compression dictionary based on compressed image, so that the compression block matched in the image is only searched in the data compression dictionary. As a result, this algorithm greatly shortens the compression time and the searching scope in the compression procedure,compared with other algorithms of the fractal block coding. In addition, the theoretical basis of constructing the data compression dictionary was obtained. Based on the new compression idea, a concrete algorithm of realizing fractal image coding was designed. The new algorithm can improve compression ratio while reducing encoding time.
Fractal compression
Fractal transform
Color Cell Compression
Texture compression
Data compression ratio
Block Truncation Coding
Lossy compression
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The demand for images, video sequences and computer animation has increased drastically over the years. This has resulted in image and video compression becoming an important issue in reducing the cost of data storage and transmission time. JPEG is currently the accepted industry standard for still image compression, but alternative methods are also being explored. Fractal Image Compression is one of them. In this paper implementation of fractal compression with quadtree partitioning have been done, this paper also includes a study of the parameters that affect fractal image compression. Keywords: fractal, compression, quadtree .
Quadtree
Fractal compression
Fractal transform
JPEG
Texture compression
Data compression ratio
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The need for multimedia applications has increased over the years. Due to this issue, image and video compression becoming an essential problem in reducing time and data storage. Fractal Image Compression (FIC) is a compression technique which results in loss, and we can have large amounts of compression. This scheme works by classifying an image into blocks and uses Contractive Mapping. Some of FICs advantages can be expressed as follows: comparing with other standard compression techniques, it has a good interchange between PNSR and compression ratio and it zooms the image without reducing the quality due to its resolution independent nature. The main FICs drawback, is its complexity in encoding and lack of speed.
Fractal compression
Fractal transform
Texture compression
Data compression ratio
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The need for multimedia applications has increased over the years. Due to this issue, image and video compression becoming an essential problem in reducing time and data storage. Fractal Image Compression (FIC) is a compression technique which results in loss, and we can have large amounts of compression. This scheme works by classifying an image into blocks and uses Contractive Mapping. Some of FICs advantages can be expressed as follows: comparing with other standard compression techniques, it has a good interchange between PNSR and compression ratio and it zooms the image without reducing the quality due to its resolution independent nature. The main FICs drawback, is its complexity in encoding and lack of speed.
Fractal compression
Fractal transform
Texture compression
Data compression ratio
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In this paper, a new fast classification strategy is proposed for fractal image compression with quadtree partitioning technique. The scheme significantly reduces the number of mean square error (MSE) computations during encoding of images. Performance in terms of compression ratios, compression time and PSNR of the fractal image compression with existing and proposed classification strategy are compared. Both techniques use quadtree partitioning scheme. The proposed classification strategy reduces the compression time significantly of the fractal image compression technique maintaining compression ratio and PSNR almost same with its counterpart.
Quadtree
Fractal compression
Fractal transform
Texture compression
Data compression ratio
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Summary form only given. The fractal image compression problem put forward three major requirements: speeding up the compression algorithm, improving image quality or increasing compression ratio. Major variants of the standard algorithm were proposed to speed up computation time. But most of them lead to a bad image quality, or a lower compression ratio. We present an implementation based on genetic algorithms. The main goal is to accelerate image compression without significant loss of image quality and with an acceptable compression rate. Results prove that genetic compression is a good choice.
Fractal compression
Fractal transform
Texture compression
Data compression ratio
Color Cell Compression
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This paper presents a new image compression method which combined the DCT with fractal image compression based on the iterated function system (IFS). Experimental results show that compared to the basic fractal image approach, the computation time is reduced and the compression ratio is improved with no decrease in in the quality of the reconstructed image.
Fractal compression
Fractal transform
Iterated function system
Texture compression
Data compression ratio
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