Consideration of illumination effects and optimization of window size for accurate calculation of depth map for 3D shape recovery
Obtaining an accurate and precise depth map is the ultimate goal for 3D shape recovery. For depth map estimation, one of the most vital parts is the initial selection of the focus measure and processing the images with the selected focus measure. Although, many focus measures have been proposed in the literature but not much attention has been paid to the factors affecting those focus measures as well as the manner the images are processed with those focus measures. In this paper, for accurate calculation of depth map, we consider the effects of illumination on the depth map as well as the selection of the window size for application of the focus measures. The resulting depth map can further be used in techniques and algorithms leading to recovery of three-dimensional structure of the object which is required in many high-level vision applications. It is shown that the illumination effects can directly result in incorrect estimation of depth map if proper window size is not selected during focus measure computation. Further, it is shown that the images need some kind of pre-processing to enhance the dark regions and shadows in the image. For this purpose, an adaptive enhancement algorithm is proposed for pre-processing. In this paper, we prove that without such pre-processing for image enhancement and without the use of proper window size for the estimation of depth maps, it is not possible to obtain the accurate depth map. (c) 2006 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
window size depth map 3d shape recovery focus measures illumination problems blurring adaptive histogram enhancement sum of modified laplacian gray-level variance shape from focus (sff)