Traditionally, fractalimage compression suffers from lengthy encoding time in measure ofhours. In this paper, combined with characteristlcs of human visual system, a flexible classification technique is proposed. Thi...
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Traditionally, fractalimage compression suffers from lengthy encoding time in measure ofhours. In this paper, combined with characteristlcs of human visual system, a flexible classification technique is proposed. This yields a corresponding adaptive algorithm which can cut down the encoding timeinto second's magnitude. Experiment results suggest that the algorithm can balance the overall encodingperformance efficiently, that is, with a higher speed and a better PSNR gain.
This paper proposes a digital watermarking scheme based on fractal image coding with DCT coefficient and needs no information about the original image. In previous work, we have proposed the digital watermarking schem...
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This paper proposes a digital watermarking scheme based on fractal image coding with DCT coefficient and needs no information about the original image. In previous work, we have proposed the digital watermarking scheme based on fractal image coding with a DCT coefficient between the range block and domain block. That scheme had high tolerance for image processing in comparison with a conventional scheme. However, it had the problem that the information about the original image used for embedding data had to be preserved for every image. In the proposal, we choose two parameters in applying fractal encoder among the respective parts, denoted as the even and odd column, so that we can extract data without resorting to the original image. Numerical experiments have been performed in order to measure the validity of the proposal. (C) 2006 Wiley Periodicals, Inc.
fractal image coding can specially utilize spatial information and self-similarity structural information of an image to achieve image super-resolution. However, fractal image coding based on single scale brings the p...
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ISBN:
(纸本)9783319093338;9783319093321
fractal image coding can specially utilize spatial information and self-similarity structural information of an image to achieve image super-resolution. However, fractal image coding based on single scale brings the problems of block effect and loss of details. In this paper we propose a multi-scale fractalcoding method for single image super-resolution. The proposed method integrates the fractal results of different scales and uses back-projection to further optimize the result. Experimental results show that the proposed method can remove the block effect, improve the loss of details and keep smooth of flat area and sharpness of edges in the reconstructed image. Compared with conventional fractalcoding and cubic splines interpolation, our method is superior to both of them subjectively and objectively.
An iteration-free fractal mating coding (IFMC) method for mutual image compression is proposed in this paper. To avoid the iteration process in the decoder, the mean image is used to generate the domain pool in both t...
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ISBN:
(纸本)9781538670361
An iteration-free fractal mating coding (IFMC) method for mutual image compression is proposed in this paper. To avoid the iteration process in the decoder, the mean image is used to generate the domain pool in both the encoder and decoder. The proposed IFMC method successfully solves the problems of long iteration duration and large memory requirement in the decoding stage in our previous fractal mating coding (FMC) method. Computer simulation results show the proposed IFMC method outperforms the previous FMC method in both the coding performance and decoding speed.
We address the problem of image superresolution and present a novel approach to single-frame superresolution using fractal image coding. The proposed approach takes great advantage of the properties of fractals-resolu...
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We address the problem of image superresolution and present a novel approach to single-frame superresolution using fractal image coding. The proposed approach takes great advantage of the properties of fractals-resolution independence, similarity preservation, and nonlinear operation-which are suited for image superresolution, specifically for image restoration and magnification. The idea of our work is to estimate the fractal code of the original image from its degraded (blurred and noised) observation and decode it at a higher resolution, and all the strategies are performed in the fractal image coding framework. To achieve this, we employ an adaptive fractalcoding scheme in the frequency domain, and further, we introduce an overlapping partition scheme to remove the blocky artifacts and improve the reconstruction quality. Experiments on simulated and real images show that the resulting fractal-based superresolution method yields superior performance to conventional single-frame superresolution methods. (C) 2008 Society of Photo-Optical Instrumentation Engineers.
The fractal image coding technique has attracted a degree of interest for its low bit rate. But the reconstructed image is of medium quality. This problem has prevented the fractal technique from being practically use...
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The fractal image coding technique has attracted a degree of interest for its low bit rate. But the reconstructed image is of medium quality. This problem has prevented the fractal technique from being practically used. In order to improve the compression fidelity, a new affine transformation is proposed in this paper. Meanwhile, its contractivity requirement is analyzed, and the optimal parameters are derived using the least square method. The new affine transformation has been practically used in imagecoding. Experiments show that the PSNR can reach 28.7dB at a compression ratio (CR) of 16.4 for the 256 x 256 x 8 "Lena" image. Comparison with other fractalcoding schemes shows that the new affine transformation can improve the reconstructed image quality efficiently.
We present a method of construction of vector valued bivariate fractal interpolation functions on random grids in R-2. Examples and applications are also included.
We present a method of construction of vector valued bivariate fractal interpolation functions on random grids in R-2. Examples and applications are also included.
Region-based functionality offered by the MPEG-4 video compression standard is also appealing for still images, for example to permit object-based queries of a still-image database. A popular method for still-image co...
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Region-based functionality offered by the MPEG-4 video compression standard is also appealing for still images, for example to permit object-based queries of a still-image database. A popular method for still-image compression is fractalcoding. However, traditional fractal image coding uses rectangular range and domain blocks. Although new schemes have been proposed that merge small blocks into irregular shapes, the merging process does not, in general, produce semantically-meaningful regions. We propose a new approach to fractal image coding that permits region-based functionalities;images are coded region by region according to a previously-computed segmentation map. We use rectangular range and domain blocks, but divide boundary blocks into segments belonging to different regions. Since this prevents the use of standard dissimilarity measure, we propose a new measure adapted to segment shape. We propose two approaches: one in the spatial and one in the transform domain. While providing additional functionality, the proposed methods perform similarly to other tested methods in terms of PSNR but often result in images that are subjectively better. Due to the limited domain-block code-book size, the new methods are faster than other fractalcoding methods tested. The results are very encouraging and show the potential of this approach for various internet and still-image database applications.
The essence of fractalimage denoising is to predict the fractal code of a noiseless image from its noisy observation. From the predicted fractal code, one can generate an estimate of the original image. We show how w...
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The essence of fractalimage denoising is to predict the fractal code of a noiseless image from its noisy observation. From the predicted fractal code, one can generate an estimate of the original image. We show how well fractal-wavelet denoising predicts parent wavelet subtress of the noiseless image. The performance of various fractal-wavelet denoising schemes (e.g., fixed partitioning, quadtree partitioning) is compared to that of some standard wavelet thresholding methods. We also examine the use of cycle spinning in fractal-based image denoising for the purpose enhancing the denoised estimates. Our experimental results show that these fractal-based image denoising methods are quite competitive with standard wavelet thresholding methods for image denoising. Finally, we compare the performance of the pixel- and wavelet-based fractal denoising schemes.
A new method for constructing recurrent bivariate fractal interpolation surfaces through points sampled on rectangular lattices is proposed. This offers the advantage of a more flexible fractal modeling compared to pr...
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A new method for constructing recurrent bivariate fractal interpolation surfaces through points sampled on rectangular lattices is proposed. This offers the advantage of a more flexible fractal modeling compared to previous fractal techniques that used affine transformations. The compression ratio for the above mentioned fractal scheme as applied to real images is higher than other fractal methods or JPEG, though not as high as JPEG2000. Theory, implementation and analytical study are also presented.
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