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High dynamic range(HDR) imaging is a technique to represent the wider range of luminance from the lightest and
darkest area of an image than normal digital imaging techniques. These techniques merge multiple images, called as
LDR(low dynamic range) or SDR(standard dynamic range) images which have proper luminance with different exposure
steps, to cover the entire dynamic range of real scenes. In the initial techniques, a series of acquisition process for LDR
images according to exposure steps are required. However, several acquisition process of LDR images induce ghost
artifact for HDR images due to moving objects. Recent researches have tried to reduce the number of LDR images with
optimal exposure steps to eliminate the ghost artifacts. Nevertheless, they still require more than three times of
acquisition processes, resulting ghosting artifacts. In this paper, we propose an HDR imaging from a single Bayer image
with arbitrary exposures without additional acquisition processes. This method first generates new LDR images which
are corresponding to each average luminance from user choices, based on Exposure LUTs(look-up tables). Since the
LUTs contains relationship between uniform-gray patches and their average luminances according to whole exposure
steps in a camera, new exposure steps for any average luminance can be easily estimated by applying average luminance
of camera-output image and corresponding exposure step to LUTs. Then, objective LDR images are generated with new
exposure steps from the current input image. Additionally, we compensate the color generation of saturated area by
considering different sensitivity of each RGB channel from neighbor pixels in the Bayer image. Resulting HDR images
are then merged by general method using captured images and estimated images for comparison. Observer's preference
test shows that HDR images from the proposed method provides similar appearance with the result images using
captured images.
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