A comparison of bicubic and biquintic interpolators suitable for real-time hardware implementation

Abstract

Digital multispectral night vision goggles incorporate both imagers and displays that often have different resolutions. While both thermal imager and micro-display technologies continue to produce larger arrays, thermal imagers still lag well behind displays and can require interpolation by a factor of 2.5 in both horizontal and vertical directions. In goggle applications, resizing the imagery streams to the size of the display must occur in real-time with minimal latency. In addition to low latency, a resizing algorithm must produce acceptable imagery, necessitating an understanding of the resized image fidelity and spatial smoothness. While both spatial and spatial frequency domain resizing techniques are available, most spatial frequency techniques require a complete frame for operation introducing unacceptable latency. Spatial domain techniques can be implemented on a neighborhood basis allowing latencies equivalent to several row clock pulses to be achieved. We have already implemented bilinear re-sampling in hardware and, while bilinear re-sampling supports moderate up-sizes with reasonable image quality, its deficiencies are apparent at interpolation ratios of two and greater. We are developing hardware implementations of both bicubic and biquintic resizing algorithms. We present the results of comparison between hardware ready versions of the bicubic and biquintic algorithms with the existing bilinear. We also discuss the hardware requirements for bicubic and biquintic compared to the existing bilinear resizing.