Abstract:  Considering the problems of low grey contrast，weak edges and noise interference for the foam image captured by the situation of the poor light in the floatation process，here is proposed a new foam image multiscale enhancement algorithm based on adaptive fractional differential and nonsubsampled contourlet transform (NSCT)． Firstly， foam image is decomposed through NSCT， the low frequency sub-band image is enhanced by combining the adaptive fractional differential order function constructed on the basis of pixel gradient feature，with the Tiansi operator which is improved by a set of brightness control parameters． Secondly，for high frequency sub-bands，threshold is adaptively computed according to the energy distribution，which is proposed to eliminate noise with the scale correlation coefficient，and the edge coefficients are enhanced by a nonlinear enhancement function． Finally， the processed image is reconstructed through NSCT． Enhancement experiment is performed by different kinds of bubble size images． Experimental results show that，compared to other current algorithms，the proposed algorithm is superior in improving the lightness，contrast，definition and comentropy of the foam image，and is successful in maintaining more texture details，which can also achieve much better performance to enhance bubble edges while removing the image noise． It lays a foundation for the subsequent foam image segmentation and edge detection．

Key words: flotation foam image, image multiscale enhancement, adaptive fractional differential, nonsubsampled contourlet transform, scale correlation coefficient