A statistical error model for image sensors and its testing

Abstract

AbstractSince images obtained from image sensor devices are commonly tested by performing a manual inspection or by means of procedures that involve large amounts of image processing, the growth in testing costs as the size of such devices increases poses a significant problem. Several approaches to automating the testing process have been proposed with a view to reducing testing costs but trial and error is needed to set the parameters required by such test procedures. In this paper we propose an error model for images taken by image sensor devices that can perform a quantitative evaluation with a small number of free parameters. Image quality testing can be performed relatively easily using this model since it replaces a previously ambiguous error model by one that can be determined uniquely. In addition, since the proposed error model is defined statistically in terms of the brightness levels of pixels in each of the individual images, even if there are individual differences between the image sensor devices, these have no influence on the testing procedure. Experimental results demonstrate that an image quality testing based on the proposed error model has the same level of accuracy as manual inspections performed by an experienced technician. © 2007 Wiley Periodicals, Inc. Syst Comp Jpn, 38(11): 1– 11, 2007; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/scj.20804