A Fast Multilevel Fuzzy Transform Image Compression Method

We present a fast algorithm that improves on the performance of the multilevel fuzzy transform image compression method. The multilevel F-transform (for short, MF-tr) algorithm is an image compression method based on fuzzy transforms that, compared to the classic fuzzy transform (F-transform) image compression method, has the advantage of being able to reconstruct an image with the required quality. However, this method can be computationally expensive in terms of execution time since, based on the compression ratio used, different iterations may be necessary in order to reconstruct the image with the required quality. To solve this problem, we propose a fast variation of the multilevel F-transform algorithm in which the optimal compression ratio is found in order to reconstruct the image in as few iterations as possible. Comparison tests show that our method reconstructs the image in at most half of the CPU time used by the MF-tr algorithm

Fuzzy Rule Based Enhancement in the SMRT Domain for Low Contrast Images

AbstractFuzzy techniques offer a new and flexible framework for the development of image enhancement algorithms. They are nonlinear, knowledge-based and robust. The potentials of fuzzy set theory for image enhancement are still not investigated in comparison with other established methodologies. In this paper, an examination of fuzzy methods in transform domain is considered. Fuzzy rule based contrast enhancement in the Sequency based Mapped RealTransform (SMRT) domain for block level processing is explored. SMRT, being an integer transform,is computationally efficient and the fuzzy rule based technique is applied to the entire blocks in the transform domain