Near-Infrared Coloring via a Contrast-Preserving Mapping Model

Near-infrared gray images captured along with corresponding visible color images have recently proven useful for image restoration and classification. This paper introduces a new coloring method to add colors to near-infrared gray images based on a contrast-preserving mapping model. A naive coloring method directly adds the colors from the visible color image to the near-infrared gray image. However, this method results in an unrealistic image because of the discrepancies in the brightness and image structure between the captured near-infrared gray image and the visible color image. To solve the discrepancy problem, first, we present a new contrast-preserving mapping model to create a new near-infrared gray image with a similar appearance in the luminance plane to the visible color image, while preserving the contrast and details of the captured near-infrared gray image. Then, we develop a method to derive realistic colors that can be added to the newly created near-infrared gray image based on the proposed contrast-preserving mapping model. Experimental results show that the proposed new method not only preserves the local contrast and details of the captured near-infrared gray image, but also transfers the realistic colors from the visible color image to the newly created near-infrared gray image. It is also shown that the proposed near-infrared coloring can be used effectively for noise and haze removal, as well as local contrast enhancement.