A Method for Enforcing Integrability in Shape from Shading Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recovering high dynamic range radiance maps from photographs
Proceedings of the 24th annual conference on Computer graphics and interactive techniques
The digital atheneum: new approaches for preserving, restoring and analyzing damaged manuscripts
Proceedings of the 1st ACM/IEEE-CS joint conference on Digital libraries
A Cylindrical Surface Model to Rectify the Bound Document Image
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Digital photography with flash and no-flash image pairs
ACM SIGGRAPH 2004 Papers
Image Restoration of Arbitrarily Warped Documents
IEEE Transactions on Pattern Analysis and Machine Intelligence
Geometric and Photometric Restoration of Distorted Documents
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
An Improved Physically-Based Method for Geometric Restoration of Distorted Document Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
A new technique for the digitization and restoration of deteriorated photographic negatives
Journal on Image and Video Processing - Special issue on image and video processing for cultural heritage
An improved HDR image synthesis algorithm
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
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The majority of early photographs were captured on acetate-based film. However, it has been determined that these negatives will deteriorate beyond repair even with proper conservation and no suitable restoration method is available without physically altering each negative. In this paper, we present an automatic method to remove various nonlinear illumination distortions caused by deteriorating photographic support material. First, using a High-Dynamic Range structured-light scanning method, a 2D Gaussian model for light transmission is estimated for each pixel of the negative image. Estimated amplitude at each pixel provides an accurate model of light transmission, but also includes regions of lower transmission caused by damaged areas. Principal Component Analysis is then used to estimate the photometric error and effectively restore the original illumination information of the negative. Using both the shift in the Gaussian light stripes between pixels and their variations in standard deviation, a 3D surface estimate is calculated. Experiments of real historical negatives show promising results for widespread implementation in memory institutions.