• Proceedings of the IEEK Conference
• /
• 1999.06a
• /
• pp.623-626
• /
• 1999

As the information society is advanced, the needs for mass information storage and retrieval grows. Digital image information is stored in retrieval systems, broadcasting in television transmission and exchanged over several kinds of telecommunication media. A major problem is that digital images are represented with large amount of data. The useful feature of image compression is that transmitting rapidly a lot of data in less time. Therefore we proposed a parallel Fractal trans-formation unit in Fractal Image compression system.

• Journal of the Institute of Convergence Signal Processing
• /
• v.3 no.1
• /
• pp.41-47
• /
• 2002

Fractal image compression can reduce the size of image data by the contractive mapping that is affine transformation to find the block(called as range block) which is the most similar to the original image. Even though fractal image compression is regarded as an efficient way to reduce the data size, it has high distortion rate and requires long encoding time. In this paper, we presented a hybrid fractal image compression system with the modified SOFM Vector Quantizer which uses improved competitive learning method. The simulation results showed that the VQ hybrid fractal using improved competitive loaming SOFM has better distortion rate than the VQ hybrid fractal using normal SOFM.

• The Transactions of the Korea Information Processing Society
• /
• v.7 no.2
• /
• pp.365-372
• /
• 2000

he paper introduces evolutionary computing to Fractal Image Compression(FIC). In Fractal Image Compression(FIC) a partitioning of the image into ranges is required. As a solution to this problem there is a propose that evolution computation should be applied in image partitionings. Here ranges are connected sets of small square image blocks. Populations consist of $N_p$ configurations, each of which is a partitioning with a fractal code. In the evolution each configuration produces $\sigma$ children who inherit their parent partitionings except for two random neighboring ranges which are merged. From the offspring the best ones are selected for the next generation population based on a fitness criterion Collage Theorem. As the optimum image includes duplication in image data, it gets smaller in saving space more efficient in speed and more capable in image quality than any other technique in which other coding is used. Fractal Image Compression(FIC) using evolution computation in multimedia image processing applies to such fields as recovery of image and animation which needs a high-quality image and a high image-compression ratio.

• Proceedings of the KIEE Conference
• /
• 1998.07g
• /
• pp.2240-2242
• /
• 1998

Image coding based on fractal theory presents highly compressed image. In this paper, we discuss about compression of Image using HV partition method. HV partition scheme devides the image adaptively in horizontal and vertical axis. And for reducing the enconding time for the domain-range comparison, we use classification scheme, which uses the order of brightness of the rectangular portion of the image. This paper focused on the technique to reduce coding time which is a problem in traditional fractal compression by adaptive selection of image and its classification method.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 1998.06a
• /
• pp.521-525
• /
• 1998

In this paper, we propose a fast algorithm for fractal image coding to shorten long time to take on fractal image encoding. For its performance evaluation, the algorithm compares with other traditional fractal coding methods. In the traditional fractal image coding methods, an original image is contracted by a factor in order to make an image to be matched. Then, the whole area of the contracted image is searched in order to find contractive transformation point of the original image corresponding to the contacted image. It needs a lot of searching time on encoding and remains limitation in the improvement of compression ratio. However, the proposed algorithm not only considerably reduces encoding tin e by using scaling method and limited search area method but also improves compression ratio by using bit-plane. When comparing the proposed algorithm with Jacquin's method, the proposed algorithm provides much shorter encoding time and better compression ratio with a little degradation of the decoded image quality than Jacquin's method.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.21 no.7
• /
• pp.1654-1667
• /
• 1996

The conventional fractal image compression methods have high computational complexity at encoding reduce PSNR at low bit rate and havehighly visible blocking effects in a reconstructed image. In this paper we propose a fractal image compression method based on disctete wavelet transform domain, which takes the absolute value of discrete wavelet transform coefficient, and assembles the discrete wavelet tranform coefficients of different highpass subbands corresponding to the same spatial block and then applies "0" encoding according to the energy of each range blocks. The proposed method improved PSNR at low bit rate and reduced computational complexity at encoding distinctly. Also, this method can achieve a blockless reconstructed image and perform hierarchical decoding without recursive constractive transformation. Computer simulations with several test images show that the proposed method shows better performance than convnetional fractal coding methods for encoding still pictures. pictures.

• The Transactions of the Korea Information Processing Society
• /
• v.4 no.1
• /
• pp.11-22
• /
• 1997

The fractal image compression partitions an original image into blocks of equal size and searches a do-main block having self-similarity. This method of compression achieves high compression ratio because it is unnecessary to transmit the additional codebook to receiver and it provides good quality of reconstructed images. In spite of these advantages, this method has a drawback in which encoding time increase due to a complicated linear transformation for determining a similar-domain block. In this paper, a fast fractal image compression method is proposed by decreasing the number of transformation usings AC(alternating current) coefficients of block. The proposed method also has a good quality as compared with the well-known fractal codings. Furthermore, method also has a good quality as apply the video steganography that can conceal an important secret data.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.21 no.3
• /
• pp.587-599
• /
• 1996

In general fractal imge compression, each range block is approximated by a contractive transform of the matching domain block under the mean squared error criterion. In this paper, a distortion measure reflecting the properties of human visual system is defined and applied to a fractal image compression. the perceptual distortion measure is obtained by multiplying the mean square error and the noise sensitivity modeled by using the background brightness and spatial masking. In order to compare the performance of the mean squared error and perceptual distortion measure, a simulation is carried out by using the 512*512 Lena and papper gray image. Compared to the results, 6%-10% compression ratio improvements under improvements under the same image quality are achieved in the perceptual distortion measure.

• Proceedings of the KOSOMBE Conference
• /
• v.1995 no.05
• /
• pp.131-134
• /
• 1995

A three dimensional fractal coding with a perceptually enhanced matching is proposed. Since most of medical images (e.g. computed tomography or magnetic resonance image) have three dimensional character, the searching region is extended to adjacent slices. For perceptually enhanced matching, a high frequency booster filter is used for prefiltering of the original image, and the least mean square error matching is applied to this edge enhanced image rather than the original image. From the simulation with the magnetic resonance images ($255{\times}255$, 8bits/pixel). the proposed algorithm provides excellent image quality with compression rations higher than 10. Compared to existing fractal coding the algorithm also provides better subjective image quality with higher compression ratio.

• Journal of Digital Contents Society
• /
• v.5 no.3
• /
• pp.199-204
• /
• 2004

A problem of many fractal image compression algorithms providing good quality at low bit rate is that the decoding time rests on an iterative procedure whose complexity is imag-dependent. This paper proposes an iterative-free fractal image decoding algorithm to reduce the decoding time. In the proposed method, under the encoder previously with the same codebook image as an initial image to be used at the decoder, the fractal coefficients are obtained through calculating the similarity between the codebook image and an input image to be encoded. As the decoding time could be remarkably reduced. For verifying the validity and universality of proposed method, We evaluated and analyzed the performance of decoding time and image quality for a number of still images and a moving picture with different distributed characteristics.