• Journal of the Korea Computer Graphics Society
• /
• v.10 no.1
• /
• pp.1-6
• /
• 2004

본 논문에서는 프랙탈 영상압축에서 화질/압축률을 향상 시키면서 압축시간을 획기적으로 향상시키는 방법을 제안한다. 본 방법은 레인지블록의 크기가 아주 작으면 유사변환 계수들의 값을 극히 제한하더라도 유사한 도메인블록을 아주 가까운 주변에서 쉽게 찾을 수 있음을 활용하여 압축시간을 단축시키고 화질/압축률을 향상 시킨다. 또한, 본 방법은 인접한 레인지블록 들의 압축에 사용되는 계수들이 좋은 상호관계를 가지도록 유도하여 화질/압축률을 더욱 향상 시킨다. 본 방법은 대부분의 프랙탈 영상압축 방법에 쉽게 적용되어 그 성능을 향상시킬 수 있다. 특히 압축시간이 전역탐색 방법에 비해서 $512{\times}512$ 영상에서 약 60000 배 $256{\times}256$ 영상에서 약 15000 배 빠르며 실시간 동영상의 I-frame에도 사용가능 하다.

• The KIPS Transactions:PartA
• /
• v.8A no.4
• /
• pp.499-502
• /
• 2001

Fractal image coding suffers from the long search time of domain pool although it provides many properties including the high compression ratio. We find that the normalized variance of a block is independent of contrast, brightness. Using this observation, we introduce a self similar block searching method employing the d-dimensional nearest neighbor searching. This method takes Ο(log/N) time for searching the self similar domain blocks for each range block where N is the number of domain blocks. PSNR (Peak Signal Noise Ratio) of this method is similar to that of the full search method that requires Ο(N) time for each range block. Moreover, the image quality of this method is independent of the number of edges in the image.

• Journal of the Korean Society of Radiology
• /
• v.13 no.4
• /
• pp.509-516
• /
• 2019

In the linear transformation method, the original image is divided into a plurality of range blocks, and a partial transform system for finding an optimal domain block existing in the image for each range block is used to adjust the performance of the compression ratio and the picture quality, The nonlinear transformation method uses only the rotation transformation among eight shuffle transforms. Since the search is performed only in the limited domain block, the coding time is faster than the linear transformation method of searching the domain block for any block in the image, Since the optimal domain block for the range block can not be selected in the image, the performance may be lower than other methods. Therefore, the nonlinear transformation method improves the performance by increasing the approximation degree of the brightness coefficient conversion instead of selecting the optimal domain block, The smaller the size of the block, the higher the PSNR value, The higher the compression ratio is increased groups were quadtree block divided to encode the image at best.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.44 no.5
• /
• pp.1-10
• /
• 2007

Most of natural images have a special property, what is called self-similarity, which is the basis of fractal image coding. Even though an image has local stationarity in several homogeneous regions, it is generally non-stationarysignal, especially in edge region. This is the main reason that poor results are induced in linear techniques. In order to overcome the difficulty we propose a non-linear technique using self-similarity in the image. In our work, an image is classified into stationary and non-stationary region with respect to sample variance. In case of stationary region, do-noising is performed as simply averaging of its neighborhoods. However, if the region is non-stationary region, stationalization is conducted as make a set of center pixels by similarity matching with respect to bMSE(block Mean Square Error). And then do-nosing is performed by Gaussian weighted averaging of center pixels of similar blocks, because the set of center pixels of similar blocks can be regarded as nearly stationary. The true image value is estimated by weighted average of the elements of the set. The experimental results show that our method has better performance and smaller variance than other methods as estimator.