Surface Reflection: Physical and Geometrical Perspectives
IEEE Transactions on Pattern Analysis and Machine Intelligence
Accurate Recovery of Three-Dimensional Shape from Image Focus
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
On the Removal of Shadows from Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shadow removal from a real image based on shadow density
SIGGRAPH '04 ACM SIGGRAPH 2004 Posters
Three-dimensional shape recovery from focused image surface
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 06
Shape from focus using multilayer feedforward neural networks
IEEE Transactions on Image Processing
A heuristic approach for finding best focused shape
IEEE Transactions on Circuits and Systems for Video Technology
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Shadows occurring in images often lead to undesirable results in computer vision. An inherent weakness of 3D reconstruction from image focus is that, they require the imaged scene to have significant textures. In many real-world applications, surfaces can be smooth and lacking in detectable texture. In such cases, Shape-form-Focus (SFF) generates inaccurate and sparse depth maps. For accurate calculation of depth map, we consider the effects of illumination. In SFF the images are taken with one light source and the shadows occur in each frame. The more bright regions of the images give more accurate depth map, whereas, the less bright regions give less accurate depth map. In this paper we propose an algorithm that removes the shadows from the image sequence which are used for SFF methods. We show the results and compare them with the previous results. From simulation results, the depth maps of objects are improved when the shadows are removed.