An endoscope is a commonly used instrument for performing minimally invasive visual examination of the tissues inside the body. A physician uses the endoscopic video images to identify tissue abnormalities. The images, however, are highly dependent on the optical properties of the endoscope and its orientation and location with respect to the tissue structure. The analysis of endoscopic video images is, therefore, purely subjective. Studies suggest that the fusion of endoscopic video images (providing color and texture information) with virtual endoscopic views (providing structural information) can be useful for assessing various pathologies for several applications: (1) surgical simulation, training, and pedagogy; (2) the creation of a database for pathologies; and (3) the building of patient-specific models. Such fusion requires both geometric and radiometric alignment of endoscopic video images in the texture space. Inconsistent estimates of texture/color of the tissue surface result in seams when multiple endoscopic video images are combined together. This paper (1) identifies the endoscope-dependent variables to be calibrated for objective and consistent estimation of surface texture/color and (2) presents an integrated set of methods to measure them. Results show that the calibration method can be successfully used to estimate objective color/texture values for simple planar scenes, whereas uncalibrated endoscopes performed very poorly for the same tests.