Comparison of adaptive linear interpolation and conventional linear interpolation for digital radiography systems

Abstract

Some large field digital radiography systems are currently under development using multiple detectors. These small size two dimension detectors are abutted together to cover a large field. Physical gaps existing between adjacent detectors produce seams between the resultant subimages. In this paper, an adaptive linear interpolation algorithm was introduced for estimating missing information at the seams and was compared with conventional linear interpolation and with nonlinear interpolation. The effectiveness of the algorithms was evaluated for relative/absolute errors. Phantom images were acquired using prototype digital radiography systems. Seams with width ranging from two pixel to six pixel were introduced and adaptive linear interpolation algorithms were applied to estimate missing information at the seams. Quantitatively, the adaptive interpolation offers at least equivalent or less error than that of the linear interpolation algorithm. The experimental results prove that there is a significant difference between two algorithms for tested radiographic images. The comparison results also show that the adaptive interpolation offers better performance than nonlinear interpolation. When developing large field digital radiography imaging systems, gaps between adjacent detectors should be minimized. For narrow seams, the adaptive linear interpolation algorithm is a practical solution because of its simplicity and effectiveness.