Reduction of ghost effect in exposure fusion by detecting the ghost pixels in saturated and non-saturated regions
This paper proposes a multiple exposure image fusion algorithm with reduced ghost. The basic idea is to adjust the weight map in the conventional fusion method in such a way that the ghost pixels are excluded. For this, pixels that cause ghost effect are detected in both of the saturated and non-saturated regions. In order to detect ghost pixels in the non-saturated region, we use the photometric relation and Gaussian mixture modeling (GMM) of a zero mean normalized cross correlation (ZNCC) map between a given exposure image and the reference. From this, we can also obtain static region where we construct an intensity mapping function (IMF) to detect the ghost pixels in saturated regions. Experimental results show that the proposed method generates high quality image without noticeable ghost effect, and yields less artifacts than the conventional methods.