A frame work for detecting the shadow and removal of the shadow from a single image in the real world pictures. Till now the work on detecting the shadows had more effort for design of hand-craft features. Shadows distroits the image in computer pictures. For instance, the decrease of performance of objects recognition and object scene analysis. This shadow inpainting technique does not perform well in the case of non-uniform shadows. In the cases of shadows in dark environments, this method does not perform well for detecting the shadow. To address these issues the frame work consists of learning the features which are relevant. The Baysian formulates so that the shadow inpainting is done efficiently. The method formulates so efficiently that the shadow detection process in shadowed part is detected and the shadowed region is obtained. The proposed method improves the image quality on curved surfaces and visual quality of photographs and real world images.

1. D. H. Hubel and T. N. Wiesel, "Receptive fields, binocular interaction and functional architecture in the cat's visual cortex," The Journal of Physiology, vol. 160, no. 1, p. 106, 1962.
2. E. Salvador, A. Cavallaro, and T. Ebrahimi, "Cast shadow segmentation using invariant color features," CVIU, vol. 95, no. 2, pp. 238–259, 2004.
3. A. J. Joshi and N. P. Papanikolopoulos, "Learning to detect moving shadows in dynamic environments," TPAMI, vol. 30, no. 11, pp. 2055–2063, 2008.
4. I. Huerta, M. Holte et al. , "Detection and removal of chromatic moving shadows in surveillance scenarios," in ICCV. IEEE, 2009, pp. 1499–1506.
5. G. D. Finlayson, S. D. Hordley, C. Lu, and M. S. Drew, "On the removal of shadows from images," TPAMI, vol. 28, no. 1, pp. 59–68, 2006.
6. G. D. Finlayson, S. D. Hordley, and M. S. Drew, "Removing shadows from images," in ECCV, vol. 2353. Springer, 2002, pp. 823–836.
7. E. Vazquez, R. Baldrich et al. , "Describing reflectances for color segmentation robust to shadows, highlights, and textures," TPAMI, vol. 33, no. 5, pp. 917–930, 2011.
8. A. Bousseau, S. Paris, and F. Durand, "User-assisted intrinsic images," in TOG, vol. 28, no. 5. ACM, 2009.
9. G. D. Finlayson, S. D. Hordley, C. Lu, and M. S. Drew, "On the removal of shadows from images," TPAMI, vol. 28, no. 1, pp. 59–68, 2006.
10. G. D. Finlayson, S. D. Hordley, and M. S. Drew, "Removing shadows from images," in ECCV, vol. 2353. Springer, 2002, pp. 823–836.
11. G. D. Finlayson, M. S. Drew, and C. Lu, "Entropy minimization for shadow removal," IJCV, vol. 85, no. 1, pp. 35–57, 2009.
12. C. Fredembach and G. D. Finlayson, "Hamiltonian path based shadow removal. " in BMVC, 2005, pp. 502–511.
13. F. Liu and M. Gleicher, "Texture-consistent shadow removal," in ECCV. Springer, 2008, pp. 437–450.
14. A. Mohan, J. Tumblin, and P. Choudhury, "Editing soft shadows in a digital photograph," Computer Graphics and Applications, IEEE, vol. 27, no. 2, pp. 23–31, 2007.
15. E. Arbel and H. Hel-Or, "Shadow removal using intensity surfaces and texture anchor points," TPAMI, vol. 33, no. 6, pp. 1202–1216, 2011.
16. V. Kwatra, M. Han, and S. Dai, "Shadow removal for aerial imagery by information theoretic intrinsic image analysis," in ICCP. IEEE, 2012, pp. 1–8.
17. John Canny. A computational approach to edge detection. Pattern Analysis and Machine Intelligence, IEEE Transactions on, PAMI-8(6):679–698, Nov. 1986.

Bayesian Shadow Inpainting Conditional Random Field Convolutional Neural Networks Shadow Inpainting.