Remote sensing image enhancement based on Shearlet transform

Remote sensing image with the characteristics of overall dim brightness, low-contrast and no obvious distinction between the target and background, makes the remote sensing image enhancement technology play an active role for improving the contrast of the image and highlighting some local details. At present, the image multi-scale system has gained successful applications in image processing, wavelet transform, Curverlet transform, Contourlet transform and some improved algorithms based on them. One of the most common shortcomings of the frameworks of the system Curverlet and Contourlet is lacking of providing a unified treatment between the continuity and the digital world. Shearlet system is the only one which satisfies this property, yet still optimally delivers sparse approximations of images. Based on Shearlet transform, we propose a new algorithm for remote sensing image enhancement. First, the remote sensing images are transformed into the low frequency coefficients and high frequent coefficients by Shearlet transform; second, we use fuzzy contrast enhancement on the low frequency coefficients of Shearlet transform; third, we use fuzzy enhancement on the high frequency coefficients of each scale and direction. Experimental results show that in the subjective side, we obtain a good visual effect, and objectively, the image entropy and mean have a significant promotion.