High dynamic range images may be created by capturing multiple images of a scene with varying exposures. Images created in this manner are prone to ghosting artifacts, which appear if there is movement in the scene at the time of capture. This paper describes a novel approach to removing ghosting artifacts from high dynamic range images, without the need for explicit object detection and motion estimation. Weights are computed iteratively and then applied to pixels to determine their contribution to the final image. We use a non-parametric model for the static part of the scene, and a pixel’s membership in this model determines its weight. In contrast to previous approaches, our technique does not rely on explicit object detection, tracking, or pixel-wise motion estimates. Ghost- and noise-free images of different scenes demonstrate the effectiveness of our technique.

Related Publications

Erum Arif Khan, Ahmet Oguz Akyuz and Erik Reinhard, 'Ghost Removal in High Dynamic Range Images', IEEE International Conference on Image Processing, Atlanta, USA, August 2006. (accepted for publication)  [pdf]

Results

In the following sequences, the first row shows the individual exposures that were used to generate the high dynamic range images. In the second row, the image on the left shows artifacts in the generated image due to ghosting and/or noise. These artifacts are reduced or removed by using our algorithm, as shown in the image on the right.

Walking Sequence

Books Sequence

Reeds Sequence

Flower Sequence