On-Line Mapping of In-Field Defects in Image Sensor Arrays

Continued increase in complexity of digital image sensors means that defects are more likely to develop in the field, but little concrete information is available on in-field defect growth. This paper presents an algorithm to help quantify the problem by identifying defects and potentially tracking defect growth. Building on previous research, this technique is extended to utilize a more realistic defect model suitable for analyzing real-world camera systems. Monte Carlo simulations show that abnormal sensitivity defects are successfully detected by analyzing only 40 typical photographs. Experimentation also indicates that this technique can be applied to imagers with up to 4% defect density, and that noisy images can be diagnosed successfully with only a small reduction in accuracy. Extension to colour imagers has been accomplished through independent analysis of colour planes of images.

• Type: Conference
• Year: 2006
• Where: DFT
• Authors: Jozsef Dudas, Cory Jung, Linda Wu, Glenn H. Chapman, Israel Koren, Zahava Koren
• Keywords: Defect Growth, DFT 2006, Hardware, In-field Defect Growth, Realistic Defect Model