Occlusion removal of faç ade texture with constrained image inpainting

Image inpainting is an effective approach to remove unwanted objects and fill holes in digital images. However, directly applying existing general-purpose digital inpainting algorithms to the correction of façade texture images with occlusions may not produce satisfactory results. This research developed a constrained image inpainting algorithm specifically designed for the correction of occluded façade texture images. The objective is to remove selected occlusions of façade texture images and restore the damaged texture blocks with reasonable textures identified with the developed constrained inpainting algorithm. In comparison with existing inpainting approaches, it can restore the occluded texture blocks more reasonably based on façade structures such as pillars, girders and window frames. Important inpainting parameters, such as window size and search area of inpainting were also investigated to achieve better inpainting results. The developed constrained inpainting algorithms were applied to real building façade images to validate their performance and to identify appropriate inpainting parameters for correcting façade texture occlusions.