In this paper are presented some results of implementation of digital watermarking methods into imagecoding based on fractal principles. The paper focuses on two possible approaches of embedding digital watermarks in...
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In this paper are presented some results of implementation of digital watermarking methods into imagecoding based on fractal principles. The paper focuses on two possible approaches of embedding digital watermarks into fractal code of images - embedding digital watermarks into parameters for position of similar blocks and coefficients of block similarity. Both algorithms were analyzed and verified on gray scale static images.
In order to improve the quality of decoded images in fractal image coding, a novel method by making use of a modified image is proposed in this paper. Since the degradation of decoded images in fractalcoding mainly c...
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ISBN:
(纸本)9781467390989
In order to improve the quality of decoded images in fractal image coding, a novel method by making use of a modified image is proposed in this paper. Since the degradation of decoded images in fractalcoding mainly comes from the poor self-similarity of the input image, a modified image that satisfies good self-similarity and approximates the original image well is constructed. After transforming the input image into the modified image and performing fractalcoding method on it, the decoded image with higher quality can be obtained. Simulations show that compared with the conventional fractalcoding method, while the same compression ratio is maintained, the proposed method can provide higher PSNR at the expense of slightly longer encoding time.
With many observations, we find that there exists a logarithmic relationship between the average collage error (ACER) and the quality of decoded images. By making use of the ACER in the encoding process, the quality o...
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ISBN:
(纸本)9781467390989
With many observations, we find that there exists a logarithmic relationship between the average collage error (ACER) and the quality of decoded images. By making use of the ACER in the encoding process, the quality of decoded images can be predicted without fractal decoding. In order to shorten the prediction process further, an accelerated version of the prediction method is proposed. By theoretical derivations and analyses, a low limit of accumulated collage error (LLPACE) is introduced which provides an effective way to evaluate the percentage of total collage error accounted by the accumulated collage error (ACE). Experiments show that for either basic fractalcoding or other three fast fractalcoding methods, the accelerated prediction method can provide satisfying performance and reduce about one third of total computations in the encoding process.
Traditional fractal image coding has a large amount of computing, whose long running time affects its realization and application. It is its blocks searching and matching that results the long time. Wavelet has multi-...
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ISBN:
(纸本)9780769537528
Traditional fractal image coding has a large amount of computing, whose long running time affects its realization and application. It is its blocks searching and matching that results the long time. Wavelet has multi-frequency characteristics, and there is self-similarity among the subimages decomposed by wavelet. Based on this, this paper's method is to reduce the redundancy of domain blocks and range blocks, and then to search and match. By this, we can largely reduce the computing time.
In this paper, we present a, classification algorithm in fractal image coding. Based on the contraction characteristics of. transformations in fractal image coding, the algorithm uses the notion of feature difference ...
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ISBN:
(纸本)0780374886
In this paper, we present a, classification algorithm in fractal image coding. Based on the contraction characteristics of. transformations in fractal image coding, the algorithm uses the notion of feature difference to speed up. the domain-range matching routine of the coding. The algorithm can effectively exclude pseudo matches during the process of domain-range matching and result in significant improvement of the rate-distortion performance. It can also be easily realized in cooperation with many other speedup schemes.
fractal image coding based on Iterated Function System (IFS) has been attracting much interest because of possibilities of drastic data compression. It achieves compression by using the self-similarity in an image. It...
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ISBN:
(纸本)0819437034
fractal image coding based on Iterated Function System (IFS) has been attracting much interest because of possibilities of drastic data compression. It achieves compression by using the self-similarity in an image. It is one of the weak points on IFS that the calculation time is huge. Especially, the amount of calculation on scaling parameter and rmse is very huge. In this paper, Ne propose two schemes to reduce the calculation time while the quality of the image is kept. The first one reduces calculation time of parameters, affine transform and rmse by using the maximum amplitude ratio which is a ratio between the maximum amplitude range of range block and that of domain block. By using the maximum amplitude ratio, domain block which does not seem to choose is excluded before calculating parameters. The second one reduces calculation time of scaling parameter by using the ratio between variance of range block and that of domain block. The variance ratio is used instead of the scaling parameter. We perform the fractal compression experiments based on the proposed schemes to verify the effectiveness of these schemes. Computational experiments show that about 50% of calculation time is reduced by using both of two schemes.
Some influential fractal methods are first discussed in this paper. Then a dual-classification technique is used to optimize the Same-Sized Block Mapping scheme, leading to considerable speed-up with no loss in fideli...
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ISBN:
(纸本)0780374886
Some influential fractal methods are first discussed in this paper. Then a dual-classification technique is used to optimize the Same-Sized Block Mapping scheme, leading to considerable speed-up with no loss in fidelity. The process of our FX(HX) scheme is also proposed in detail. Finally, the good performance can be seen in experimental results.
Lossless fractal image coding (LFIC) is a new method to code images. The significant property of this method is that it is the first simple fractal image coding method that can regenerate images without data loss (los...
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ISBN:
(纸本)9531840547
Lossless fractal image coding (LFIC) is a new method to code images. The significant property of this method is that it is the first simple fractal image coding method that can regenerate images without data loss (lossless). The method, different from the other fractalimage compression [1][2], needs no search for matched domain-range. Therefore, the coding time of this method is also very fast compared with the other fractalimage compression methods.
In order to improve the performance of fractalcoding methods, a new method is proposed in this paper. Firstly, we find that the range blocks with large variances play a more important role in causing the degradation ...
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ISBN:
(纸本)9789811365041;9789811365034
In order to improve the performance of fractalcoding methods, a new method is proposed in this paper. Firstly, we find that the range blocks with large variances play a more important role in causing the degradation of decoded images, and the effect of the remaining range blocks can be ignored. Secondly, the range blocks with larger variances will be encoded in an extended domain block pool, and the remaining ones will be encoded with the no-search fractal encoding method. Finally, two fractalcoding methods are used to assess the performance of the proposed method. Experiments show that compared with the previous methods, the proposed method can provide shorter encoding time, better quality of decoded images and fewer bits per pixel.
fractalimage compression is a lossy imagecoding method using partitioned iterated function systems (PIFS). Compared with rapid decompression algorithms, the compression process is extremely time-consuming, so how to...
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ISBN:
(纸本)0780374886
fractalimage compression is a lossy imagecoding method using partitioned iterated function systems (PIFS). Compared with rapid decompression algorithms, the compression process is extremely time-consuming, so how to speed up the compression procedure remains a challenging issue. The most common solution involves classification of domain and range blocks according to features, after which matches across class boundaries are excluded. In this paper, we compare two feature vector methods-mass center and box dimension. Experimental results demonstrate the improvements in compression performance.
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