Combining High-Resolution Images With Low-Quality Videos
Franz Schubert, Krystian Mikolajczyk · 2008
Recently a lot of research has been directed towards the question: What can be done with "brute-force vision" using huge amounts of data?Image retrieval methods have been shown to succeed on collections of images with sizes over a million.Various applications such as object recognition, 3D geometrical arrangment of images showing the same scene or inferring missing image regions can benefit from large image databases.Motivated by this research we propose an alternative use of image information stored in large pools like the internet.Given an input video, we can utilize corresponding still images stored at much better quality to improve the overall quality of the video.A hybrid superresolution scheme is applied to smoothly incorporate the high-frequency components.On those areas where hallucination of details fails, a standard MAP-estimation of the high-resolution image is performed.The performance is demonstrated on real data examples.