Adaptive Gamma Processing of the Video Camera for the Expansion of the Dynamic Range

Abstract

We have developed a new signal processing method for expanding the dynamic range of a video camera. A variable and nonlinear gamma characteristic is applied to the input image depending on the distribution of the luminance. We set the gamma characteristic for the back-lit images so as to amplify the luminance of the dark pixels and preserve the contrast of the bright pixels. We have established the decision rule of the gamma characteristic using the learning algorithms of neural networks in order to make the decision rule correspond human vision. The implementation of the gamma decision rule consists of a cascade connection of RAMs, which decreases the required total capacity of RAMs by 1/100 compared with the implementation with a single RAM. The effect of our new method is expand the dynamic range by three times.