Analyzing the Impact of ISO on Digital Imager Defects with an Automated Defect Trace Algorithm

Reliability of image sensors is limited by the continuous development of in-field defects. Laboratory calibration on 21 DSLRs has revealed hot pixels as the main defect type found in all tested cameras, with 78% of the identified defects having a time-independent offset. The expanded ISO range that exists in new cameras enables natural light photography. However, the gain applied to all pixels also enhances the appearance of defects. Analysis of defects at varying ISO levels shows that compared to the number of defects at ISO 400, the number of defects at ISO 1600 is 2-3 times higher. Amplifying the defect parameters helps differentiate faults from noise, thus detecting larger defect sets and causes some hot pixels to become saturated. The distribution of defect parameters at various ISO levels shows that the gain applied to faults with moderate defect magnitude caused 2-10% of the defects to saturate at short exposure times (0.03-0.5s). With our expanded defect collection, spatial analysis confirmed the uniform distribution of defects, indicating a random defect source. In our extended study, the temporal growth of defects is analyzed using our defecttracing algorithm. We introduce an improved defect model which incorporates the ISO gain, allowing the detection of defects even in short exposure images at high ISO and thus providing a wider selection of historical images and more accurate defect tracing. Larger area sensors show more hot pixels, while hot pixel rates strongly grow as the pixel size decreases to 2.2 microns.