  Combining images with different exposure settings are of prime importance in
the field of computational photography. Both transform domain approach and
filtering based approaches are possible for fusing multiple exposure images, to
obtain the well-exposed image. We propose a Discrete Cosine Transform
(DCT-based) approach for fusing multiple exposure images. The input image stack
is processed in the transform domain by an averaging operation and the inverse
transform is performed on the averaged image obtained to generate the fusion of
multiple exposure image. The experimental observation leads us to the
conjecture that the obtained DCT coefficients are indicators of parameters to
measure well-exposedness, contrast and saturation as specified in the
traditional exposure fusion based approach and the averaging performed
indicates equal weights assigned to the DCT coefficients in this non-parametric
and non pyramidal approach to fuse the multiple exposure stack.
