Aerial photography restoration using the maximum likelihood estimator (MLE) algorithm

Ignacio Juvells Prades; Jorge Nunez; Fernando Perez; Vincenc Pala; Roman Arbiol

doi:10.1117/12.182866

17 August 1994 Aerial photography restoration using the maximum likelihood estimator (MLE) algorithm

Ignacio Juvells Prades, Jorge Nunez, Fernando Perez, Vincenc Pala, Roman Arbiol

Proceedings Volume 2357, ISPRS Commission III Symposium: Spatial Information from Digital Photogrammetry and Computer Vision; (1994) https://doi.org/10.1117/12.182866
Event: Spatial Information from Digital Photogrammetry and Computer Vision: ISPRS Commission III Symposium, 1994, Munich, Germany

Abstract

We apply the maximum likelihood estimator (MLE) method to restore scanned photogrammetric plates. In color images, the restoration is carried out separately for each band. To compute the MLE solution, we use the algorithm based on the expectation maximization (EM) algorithm for Poisson data. The memory and CPU time needed to obtain MLE solutions make feasible the restoration of images of 512 X 512 or 1024 X 1024 pixels, but the restoration of a series of large scanned photographs, as happens with photogrammetric plates, is not of practical use with present-day computers. With the aim of bypassing this problem, several 512 X 512 portions of the plate are extracted and restored with the MLE algorithm. Then, the convolution function transforming the original into the restored image is calculated in Fourier space, thus obtaining a convolution matrix when returning to normal space. Next, this matrix is truncated and a convolution is performed over the whole image. A series of tests over the same image digitized with different scanners has been carried out to separate this contribution from environmental effects.

Citation Download Citation

Ignacio Juvells Prades, Jorge Nunez, Fernando Perez, Vincenc Pala, and Roman Arbiol "Aerial photography restoration using the maximum likelihood estimator (MLE) algorithm", Proc. SPIE 2357, ISPRS Commission III Symposium: Spatial Information from Digital Photogrammetry and Computer Vision, (17 August 1994); https://doi.org/10.1117/12.182866

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