Near-Infrared Coloring via a Contrast-Preserving Mapping Model

作者：Son Chang Hwan^*; Zhang Xiao Ping

来源：IEEE Transactions on Image Processing, 2017, 26(11): 5381-5394.

DOI：10.1109/TIP.2017.2724241

• Coloring
• color transfer
• contrast enhancement
• denoising
• dehazing
• image fusion
• near-infrared imaging

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 nearinfrared 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 nearinfrared 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.

• 出版日期2017-11