Measuring the effectiveness of bad pixel detection algorithms using the ROC curve

Digital camera sensors usually contain defective pixels that either arise during the manufacturing process, or develop over time. These defects though small in number, are very noticeable to an experienced eye when looking at images captured from the camera. As a result it becomes extremely important for the sensor manufacturing companies to develop methods which would reduce these manufacturing errors. There have been a number of algorithms proposed for online detection of sensor defects in the literature, but there is no standard method of fairly comparing algorithms given that each algorithm uses thresholds in a different way. This paper presents a novel idea which makes use of the Receiver Operating Characteristics (ROC) curve for comparison among the various bad pixel correction algorithms. We demonstrate how the characteristics of the ROC curve can be used for determining the effectiveness of the algorithms and hence help us to decide which of the algorithms perform better than the others. Experimental results comparing two such bad pixel detection algorithms are provided¹.