针对Jacquin分形编码算法中选取的相似块数目较少，从而与图象块匹配的效率不高的缺点，提出了通过线性旋转变换来扩充相似块数目，以进行最佳匹配的分形编码方法，与通常方法不同，为了充分发掘图象自身的相似性，该方法首先在图象中的多个方向上选取相似块，然后通过对称变换和线性旋转变换生成新的相似块集来进行编码，当旋转方向数取4时，就可以将Jacquin提出的Isometries变换归结为该方法的一种特例，通过调整旋转方向的数目，能有效地改善Isometries变换相似块数目不足的缺点，并得到了较优的压缩结果。另外，针对线性旋转变换还提出了基于查找表的加速算法，从而显著减少了编码时间。

Because the number of domain blocks is not sufficient in the Jacquin's fractal image coding method, the matching between domain blocks and range blocks is not very effective. To improve the matching efficiency, this paper puts forward a new fractal image coding method, which increases the number of domain blocks through linear rotation transforms and gets the optimal matching. Unlike in the ordinary methods, in order to exploit fully the self similarity in the image, this method chooses domain blocks from multiple directions in the image, then generates new sets of domain blocks through a symmetric transform and linear rotation transforms. The Isometries transforms proposed by Jacquin can be viewed as a special case of this method when the rotation direction number is fixed to 4. This method modifies the number of rotation directions, thus amends for the inadequacy of domain blocks in the Isometries transforms, and gets a better compression result. An acceleration algorithm based on a lookup table is also established for the linear rotation transforms, which effectively shortens the encoding time.