Uneven illumination removal and image enhancement using empirical mode decomposition

Abstract

Uneven light distribution problems often arise in poorly scanned text or text-photo images and natural images taken by digital camera. An innovative image-processing technique for uneven illumination removal using empirical mode decomposition (EMD) is proposed. The EMD is local, adaptive, and useful for analyzing nonlinear and nonstationary signals. In this method, we decompose images by EMD and get the background level locally and adaptively. This algorithm can enhance the local reflectance in the image while removing uneven illumination for black/white text images, text-photo images, and natural color/gray-level images. The proposed technique can be very helpful for image and text recognition. The EMD can also be applied to the three color channels (RGB) of color images separately to estimate the reflectances of the three color channels. After we relight these channels using white light and the estimated reflectances, a simple color constancy task can be performed to correct certain poorly lighted color images. Our technique is compared with recently proposed methods for correcting images with uneven illumination and the experimental results demonstrated that the proposed approach can effectively enhance natural color/gray-level images and make text and text-photo images more readable under uneven illumination.