UC San Diego

Dual energy imaging is a technique whereby an object is scanned with X-rays of two levels of energies to extract information about the object's atomic composition (Z). This technique is based on the fact that the X-ray absorption coefficient decreases with X-ray energy for low -Z materials, but begins to increase for high-Z materials due to the onset of pair production. Methods using the ratio of the attenuations for high-energy to low-energy images as an indicator of Z value have been proposed by several people. However, the statistical errors associated with the systems make those indicators unreliable. This thesis will discuss the problems associated with using a dual-energy system for high-atomic-number material (also known as high Z material) detection. We will identify the sources of noise that hinder system performance and propose solutions for noise reduction. Later chapters will deal with methods to automate the high Z detection process. We use a method called adaptive masking to identify possible high Z objects and reduce the false alarms. For objects shielded by materials common in a cargo container, we propose a layer separation approach to estimate the ratio of the high-and low-energy attenuations of the shielded objects. The approaches provided in this thesis are able to enhance the detection rate and reduce the false alarms significantly