Cervical intraepithelial neoplasia (CIN) exhibits certain morphologic features that can be identified during a colposcopic exam. Immature metaplastic and dysplastic cervical squamous epithelia turn white after application of acetic acid during the exam. The whitening process occurs visually over several minutes and subjectively helps to discriminate between dysplastic and normal tissue. Digital imaging technologies enable us to assist the physician in analyzing acetowhite (acetic-acid-induced) lesions in a fully automatic way. We report a study designed to measure multiple parameters of the acetowhitening process from two images captured with a digital colposcope. One image is captured before the acetic acid application, and the other is captured after the acetic acid application. The spatial change of the acetowhitening is extracted using color and texture information in the post-acetic-acid image; the temporal change is extracted from the intensity and color changes between the post-acetic-acid and pre-acetic-acid images with an automatic alignment. In particular, we propose an automatic means to calculate an opacity index that indicates the grades of temporal change. The imaging and data analysis system is evaluated with a total of 99 human subjects. The proposed opacity index demonstrates a sensitivity and specificity of 94 and 87%, respectively, for discriminating high-grade dysplasia (CIN2+) from normal and low-grade subjects, considering histology as the gold standard.