Adaptive Smoothness Constraint Image Multilevel Fuzzy Enhancement Algorithm

For the problems of poor enhancement effect and long lime consuming of the traditional algorithm, an adaptive smoothness constraint image multilevel:fizzy enhancement algorithm based on secondary color-to-grayscale conversion is proposed By using fuzzy set theory and generalized fuzzy set theory, a new linear generalized fuzzy operator transformation is carried out to obtain a new linear generalized fuzzy operator. By using linear generalized membership transformation and inverse transformation, secondary color-to-grayscale conversion of adaptive smoothness constraint image is performed Combined with generalized fuzzy operator, the region contrast fuzzy enhancement of adaptive smoothness constraint image is realized, and image multilevel fuzzy enhancement is realized Experimental results show that the fuzzy degree of the image is reduced by the improved algorithm, and the clarity of the adaptive smoothness constraint image is improved effectively. The time consuming is short, and it has some advantages.