In this paper, we study the hot issues of fractal image encoding.
本文对分形图像编码的热点问题进行了研究。
This paper proposes a correlation-coefficients-based scheme for fast fractal image encoding, which does not need to change the existing fractal decoding procedure.
该文提出了快速分形图像编码的一种基于相关系数的编码方案，不需要改变现有的分形解码过程。
Thus, encoding an image by fractal techniques consists of finding an appropriate contractive transformation whose fixed point is the best possible approximation of the original image.
因此，一幅图像的分形编码就是寻找一个合适的压缩仿射变换，它的不动点是原始图像尽可能好的近似。
The nowadays fractal image compression schemes suffers from long encoding time, because of considerable comparisons with domain blocks for each range block to find its best-match domain blocks.
目前分形图像压缩的最主要问题是其编码时间太长，这主要是因为在分形编码时，对每一个待编码值域块都需要比较数量巨大的定义域块才能找到它的最优匹配块。
Fractal image coding is a very promising compression technique, but it suffers from long encoding time.
分形图像编码是一种很有前途的压缩技术，但编码时间长阻碍了它的广泛应用。
This paper proposed an improved scheme for fractal image coding by introducing a control parameter that can affect the decoded image quality as well as encoding speed.
通过引入一个可以影响解码图像质量和编码时间的控制参数，该文提出了分形图像编码的一种改进方案。
Fractal image compression is of outstanding advantages of high compression ratio and high image qualities, but its encoding process is time-consuming.
分形图象编码法具有高压缩比、高图象品质等显著优点，但其编码时间太长。
Fractal image compression is of outstanding advantages of high compression ratio and high image qualities, but its encoding process is time-consuming.
分形图象编码法具有高压缩比、高图象品质等显著优点，但其编码时间太长。
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