Remote Sensing Image Enhancement Using Regularized-Histogram Equalization and DCT

Xueyang Fu, Jiye Wang, Delu Zeng, Yue Huang, Xinghao Ding

Abstract: In this letter, an effective enhancement method for remote sensing images is introduced to improve the global contrast and the local details. The proposed method constitutes an empirical approach by using the regularized-histogram equalization (HE) and the discrete cosine transform (DCT) to improve the image quality. First, a new global contrast enhancement method by regularizing the input histogram is introduced. More specifically, this technique uses the sigmoid function and the histogram to generate a distribution function for the input image. The distribution function is then used to produce a new image with improved global contrast by adopting the standard lookup table-based HE technique. Second, the DCT coefficients of the previous contrast improved image are automatically adjusted to further enhance the local details of the image. Compared with conventional methods, the proposed method can generate enhanced remote sensing images with higher contrast and richer details without introducing saturation artifacts.