958 research outputs found
RIBBONS: Rapid Inpainting Based on Browsing of Neighborhood Statistics
Image inpainting refers to filling missing places in images using neighboring
pixels. It also has many applications in different tasks of image processing.
Most of these applications enhance the image quality by significant unwanted
changes or even elimination of some existing pixels. These changes require
considerable computational complexities which in turn results in remarkable
processing time. In this paper we propose a fast inpainting algorithm called
RIBBONS based on selection of patches around each missing pixel. This would
accelerate the execution speed and the capability of online frame inpainting in
video. The applied cost-function is a combination of statistical and spatial
features in all neighboring pixels. We evaluate some candidate patches using
the proposed cost function and minimize it to achieve the final patch.
Experimental results show the higher speed of 'Ribbons' in comparison with
previous methods while being comparable in terms of PSNR and SSIM for the
images in MISC dataset
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