With the advancements in iris matching and growing number of system deployments, a wide variety of iris cameras are now being manufactured. These cameras differ in manufacturing technology, including image acquisition spectrum and illumination settings. For large scale applications (e.g. UID system in India) where cameras from several vendors are likely to be used for iris enrollment and authentication, iris camera interoperability is an important consideration. The question we address here is: will the matching accuracy differ in matching iris images captured by two different cameras compared to images captured by the same camera? We propose an iris camera classification-based preprocessing framework to address iris interoperability. The camera classification output is used to perform selective iris image enhancement. Experimental results on the IIITD Multi-Sensor Iris database collected locally and the Notre Dame Cross Sensor database show a significant improvement in the cross-camera iris recognition accuracy using the proposed approach. © 2012 IEEE.