Enhanced Fractal Coding Method Using Candidate Transformations

This paper presents a new fractal coding scheme to find more optimal transformation by estimation of the optimal attractor. The conventional fractal coding schemes based on the collage theorem obtain the transformation to minimize the distance between an original image and its collage image. Heavy computation is why the schemes widely adopt the theorem. In other words, the optimal transformation can be obtained after the attractors of all the possible transformations are generated and then compared with an original image. It is clear that this process is not practical. Therefore, we introduce a sub-optimal scheme that provides better transformation than the conventional scheme, relieving the complexity problem in the optimal transformation. In a simple case, the optimal transformation can be obtained considering all the attractors and then our scheme is compared with the optimal. In general cases not to be able to find the optimal, our scheme is also evaluated and compared with the conventional schemes.