An efficient remote sensing image compensation method based on assessed modulated transfer function

In the acquisition process of a remote sensing image, remote sensing image quality degradation is caused by fuzzy and noise. However, how to compensate the image degradation remains a crucial but unsolved issue until now. In this work, we propose an efficient remote sensing image compensation method based on assessed modulated transfer function (MTF). First, the MTF is assessed from multiple edge sub-images. We use homomorphic filter algorithm to enhance the local sub-image because the MTF extraction process needs high quality image. The added enhancement filter makes the assessed MTF not consistent with the original one. Based on this condition, we adopt a second-filter algorithm to perform the image compensation. Experiments confirm that the proposed method is enough good, and it can obtain the better detailed information and visual effect than before compensation.