tailieunhanh - Báo cáo hóa học: " Research Article Overcoming Registration Uncertainty in Image Super-Resolution: Maximize or Marginalize?"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Overcoming Registration Uncertainty in Image Super-Resolution: Maximize or Marginalize? | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2007 Article ID 23565 14 pages doi 2007 23565 Research Article Overcoming Registration Uncertainty in Image Super-Resolution Maximize or Marginalize Lyndsey C. Pickup David P. Capel Stephen J. Roberts and Andrew Zisserman Information Engineering Building Department of Engineering Science Parks Road Oxford OX1 3PJ UK Received 15 September 2006 Accepted 4 May 2007 Recommended by Russell C. Hardie In multiple-image super-resolution a high-resolution image is estimated from a number of lower-resolution images. This usually involves computing the parameters of a generative imaging model such as geometric and photometric registration and blur and obtaining a MAP estimate by minimizing a cost function including an appropriate prior. Two alternative approaches are examined. First both registrations and the super-resolution image are found simultaneously using a joint MAP optimization. Second we perform Bayesian integration over the unknown image registration parameters deriving a cost function whose only variables of interest are the pixel values of the super-resolution image. We also introduce a scheme to learn the parameters of the image prior as part of the super-resolution algorithm. We show examples on a number of real sequences including multiple stills digital video and DVDs of movies. Copyright 2007 Lyndsey C. Pickup et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. 1. INTRODUCTION Multiframe image super-resolution refers to the process by which a set of images of the same scene are fused to produce an image or images with a higher spatial resolution or with more visible detail in the high spatial frequency features 1 . The limits on the resolution of the original imaging device can be improved by .

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