Gradient-Based Correction of Chromatic Aberration in the Joint Acquisition of Color and Near-Infrared Images

Chromatic aberration distortions, such as wavelength-dependent blur caused by imperfections in photographic lenses, have long been studied in color imaging. The problem becomes more challenging to solve in the case of color and near-infrared joint acquisition, as a wider range of wavelengths is captured. In this paper, we assume that the color image is in focus, hence, the NIR image captured with the same focus settings is blurred. We propose an algorithm that estimates the blur kernel and deblurs the NIR image, using the in-focus color image as a guide in both steps. In the deblurring step, we retrieve the lost details of the NIR image by using the sharp edges of the color image. The main diculty in this task is caused by the fact that the edges of color and NIR images are not always correlated. To handle this issue, the algorithm analyzes the dierences between the gradients of NIR and color channels. Simulation results verify the eectiveness of our algorithm, both in estimating the blur kernel and deblurring the NIR image, without producing ringing artifacts inherent to the results of other deblurring methods.