Single Band Night Vision Image Texture Based Colorization

Infra-red (IR) image colorization has always been a challenging goal. Reducing human error and speeding up reaction time are just some of the benefits achieved by this process. However, essential differences exist between IR, which are temperature dependent sensors, and regular color visible light ones. These differences cause difficulties when trying to use color images in the rendering process. In this paper we present an implementation of a novel method for automatically coloring IR images. The method uses a reference (source) color image which is selected from a database by a texture-descriptor algorithm, searching for resemblance to the IR (target) image. Next, by dividing the images into main texture segments and assigning local characteristics, a best matching color pixel is found per IR pixel. As opposed to other methods, the color pixels are clustered in every segment to form a palette, and not randomly selected. This process expresses global as well as local features of each pixel and causes the transferred color to appear more accurate. Results show that our method produced more natural looking images than achieved heretofore.


Tomer Hamam, Yedidyah Dordek and Deborah Cohen, Single-Band Infrared Texture-Based Image Colorization, 27th IEEE Convention of Electrical and Electronics Engineers in Israel 2012, Eilat, Israel.