Restoration of Noisy and Noiseless Fence Occlusion Images
M. Varalakshmamma, Tangala Venkateswarlu · Pattern Recognition and Image Analysis · 2020
Abstract A new approach is presented to restore the image from noisy fence images. When people capture the images at Zoos, parks and gardens the fence affects the authentic appeal of the object behind it. Due to the acquisition channels, the noise will be added to the images. So, removal of the fence and noise in these images is necessary to improve the appearance of the desired objects. Segmentation of the fence from the noisy image is very difficult because these are extended into the entire image region. In this paper, segmentation of the fence is done in both noiseless and Gaussian noise corrupted images. Segmentation of the fence is achieved using a graph cut technique. Morphological operations are applied to improve the fence mask. Removal of the fence is done with a hybrid inpainting technique. From the De-fenced image, noise is removed using Conventional Neural Networks. Qualitative and quantitative results show the effectiveness of the proposed approach.