Degraded image enhancement with applications in robot vision

The theory of fuzzy sets has been used to deal with image enhancement problems for degraded images in which the image edges are uncertain and inaccurate. For those kinds of images, to some extent, the good enhancement effect can be obtained using the fuzzy sets-based image enhancement method instead of the traditional image enhancement approaches. The gray level maximum has not been changed in the classical fuzzy enhancement method proposed by S. K. Pal, so this method is not fit for the enhancement problem of degraded images with less gray levels and low contrasts; the fact that the range of membership function of gray levels is not normalization form, i.e. [0,1], is another disadvantage of the traditional fuzzy enhancement approach. To deal with the problems mentioned above, a generalized iterative fuzzy enhancement algorithm is proposed in this paper. A new image quality assessment criterion is suggested on the basis of the statistical features of the gray-level histogram of images to control the iterative procedure of the proposed image enhancement algorithm. Computer simulation results showed that this new enhancement method is more suitable than fuzzy enhancement and gray-level transformation for handling the enhancement problems of images with less gray levels and low contrasts.