Image inpainting is the process of filling in of missing region so as to preserve its overall continuity. Image inpainting is manipulation and modification of an image in a form that is not easily detected. Digital image inpainting is relatively new area of research, but numerous and different approaches to tackle the inpainting problem have been proposed since the concept was first introduced. This paper analyzes and compares two recent exemplar based inpainting algorithms by Zhaolin Lu et al and Hao Guo et al. A number of examples on real images are demonstrated to evaluate the results of algorithms using Peak Signal to Noise Ratio (PSNR).
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