Image motion restoration from a sequence of images

Ofer Hadar; M. Robbins; Y. Novogrozky; D. Kaplan; Stanley R. Rotman; Norman S. Kopeika

doi:10.1117/12.210428

26 May 1995 Image motion restoration from a sequence of images

Ofer Hadar, M. Robbins, Y. Novogrozky, D. Kaplan, Stanley R. Rotman, Norman S. Kopeika

Proceedings Volume 2468, Acquisition, Tracking, and Pointing IX; (1995) https://doi.org/10.1117/12.210428
Event: SPIE's 1995 Symposium on OE/Aerospace Sensing and Dual Use Photonics, 1995, Orlando, FL, United States

Abstract

This paper deals with the restoration of images blurred as a result of image motion or vibration. The key for restoration algorithm success is to derive accurately the Optical Transfer Function (OTF) representing the image motion degradation in the spatial frequency domain. The basic method of obtaining the OTF from the relative displacement between the camera and the object using a motion sensor has been developed recently and is discussed elsewhere. In this paper, the motion function is derived instead from analysis of a sequence of images. The first step is to obtain the image motion information from the sequence of images according to two well known algorithms - the Block Matching Algorithm (BMA) and Edge Trace Tracking (ETT). The basis for these two methods consists of tracking a block or an edge through a sequence of several images. The results of these two methods were fitted to a sinusoidal function, compared, and there was excellent agreement between them. Finally, the image is restored using the OTF obtained from the tracking method.

Citation Download Citation

Ofer Hadar, M. Robbins, Y. Novogrozky, D. Kaplan, Stanley R. Rotman, and Norman S. Kopeika "Image motion restoration from a sequence of images", Proc. SPIE 2468, Acquisition, Tracking, and Pointing IX, (26 May 1995); https://doi.org/10.1117/12.210428

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KEYWORDS

Optical transfer functions

Filtering (signal processing)

Cameras

Image restoration

Electronic filtering

Image processing

Motion estimation

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