Efficient Color Reproduction Algorithm for Endoscopic Images Based on Dynamic Color Map

Improved visual quality and color information in endoscopic images play an important role in diagnosing various gastrointestinal (GI)-tract-related diseases. This paper presents a grayscale-to-color image reproduction method, which is preceded by a pre-processing scheme, for endoscopic images. The color reproduction is achieved by generating a dictionary-based color mapping from a theme color image and then applying it to the pre-processed grayscale image. The theme color image is chosen from a nearby GI tract location of the input grayscale image so that the generated output color image contains similar color tone. The color map is dynamic as its contents change with the change of the theme image. The proposed method is used on low-contrast grayscale white light images and raw narrow band images to highlight the vascular and mucosa structures and to colorize the images. The method is also used to colorize grayscale video sequences of wireless capsule endoscopy. Based on the statistic visual representation, the proposed method can better highlight the mucosa structure compared to other methods. The color similarity was verified using the delta E color difference, structure similarity index, mean structure similarity index, and structure and hue similarity. The proposed algorithm has low and linear time complexity, which results in higher execution speed than those of related works. Finally, the quality of the generated color images was verified visually by several professional gastroenterologists, whose mean opinion score is presented.