Tobias Bergen1, Thomas Wittenberg2, Christian Münzenmayer2. 1. Fraunhofer Institute for Integrated Circuits IIS, Erlangen, Germany. tobias.bergen@iis.fraunhofer.de. 2. Fraunhofer Institute for Integrated Circuits IIS, Erlangen, Germany.
Abstract
PURPOSE: Inhomogeneous illumination often causes significant shading and vignetting effects in images captured by an endoscope. Most of the established shading correction methods are designed for gray-level images. Only few papers have been published about how to compensate for shading in color images. For endoscopic images with a distinct red coloring, these methods tend to produce color artifacts. METHOD: A color shading correction algorithm for endoscopic images is proposed. Principal component analysis is used to calculate an appropriate estimate of the shading effect so that a one-channel shading correction can be applied without producing undesired artifacts. RESULTS: The proposed method is compared to established YUV and HSV color-conversion-based approaches. It produces superior results both on simulated and on real endoscopic images. Example images of using the proposed shading correction for endoscopic image mosaicking are presented. CONCLUSION: A new method for shading correction is presented which is tailored to images with distinct coloring. It is beneficial for the visual impression and further image analysis tasks.
PURPOSE: Inhomogeneous illumination often causes significant shading and vignetting effects in images captured by an endoscope. Most of the established shading correction methods are designed for gray-level images. Only few papers have been published about how to compensate for shading in color images. For endoscopic images with a distinct red coloring, these methods tend to produce color artifacts. METHOD: A color shading correction algorithm for endoscopic images is proposed. Principal component analysis is used to calculate an appropriate estimate of the shading effect so that a one-channel shading correction can be applied without producing undesired artifacts. RESULTS: The proposed method is compared to established YUV and HSV color-conversion-based approaches. It produces superior results both on simulated and on real endoscopic images. Example images of using the proposed shading correction for endoscopic image mosaicking are presented. CONCLUSION: A new method for shading correction is presented which is tailored to images with distinct coloring. It is beneficial for the visual impression and further image analysis tasks.
Entities:
Keywords:
Color shading correction; De-vignetting; Endoscopy; Image stitching; Principal component analysis