Estimation of Low Dynamic Range Images from Single Bayer Image using Exposure Look-up Table for High Dynamic Range image

摘要

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.