Towards real-time hardware gamma correction for dynamic contrast enhancement

Making the transition between digital video imagery acquired by a focal plane array and imagery useful to a human operator is not a simple process. The focal plane array ?sees? the world in a fundamentally different way than the human eye. Gamma correction has been historically used to help bridge the gap. The gamma correction process is a non-linear mapping of intensity from input to output where the parameter gamma can be adjusted to improve the imagery´s visual appeal. In analog video systems, gamma correction is performed with analog circuitry and is adjusted manually. With a digital video stream, gamma correction can be provided using mathematical operations in a digital circuit. In addition to manual control, gamma correction can also be automatically adjusted to compensate for changes in the scene. We are interested in applying automatic gamma correction in systems such as night vision goggles where both low latency and power efficiency are important design parameters. We present our results in developing an automatic gamma correction algorithm to meet these requirements. The algorithm is comprised of two parts, determination of the desired value for gamma and the application of the correction. The calculation of the gamma value update is performed based upon statistical metrics of the imagery´s intensity. HDL code implementing the measurement of the statistical metrics has been developed and tested in hardware. Both the computation of a gamma update and the application of the gamma correction were simplified to basic arithmetic operations and two specialized functions, logarithm and exponentiation of a constant base by a variable exponent. We present approximation methods for both specialized functions simplifying their implementation into basic arithmetic operations. The hardware implementations of the approximations allow the above requirements to be met. We evaluate the accuracy of the approximations as compared to full resolution double-precision float- - ing point mathematical operations. We present the final results for visual judging to evaluate the impact of the approximations.