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Advanced Image Restoration Techniques Using Entropy Maximization for Wireless Sensor Calibration

This research explores innovative approaches to image restoration, focusing on the reconstruction of original images from degraded observations. The key concept involves the application of entropy maximization under constraints to improve restoration quality. We discuss both unconstrained and constrained restoration methodologies, demonstrating their relevance to calibrating wireless sensor networks. The effectiveness of these classical methods for blind and non-blind calibration is also highlighted. This work builds upon prior foundational studies, contributing to the advancement of image processing in practical applications.

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Advanced Image Restoration Techniques Using Entropy Maximization for Wireless Sensor Calibration

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  1. Research Idea Lei Rao Feb. 7th, 2009

  2. Basic Idea of Image Restoration g (x, y) Degradation Function H Restoration Filter (s) f (x, y) + f* (x, y) Noise n (x, y) • Question: How to reconstruct the original image f (x, y) from the observation g (x, y)? • Algebraic Approach to Restoration: • Unconstrained Restoration • Constrained Restoration • Idea: • Entropy Maximization under Constraints reconstructs the image better.

  3. Related Work [1] S. Burch, S. Gull, and J. Skilling, “Image restoration by a powerful maximum entropy method,” Computer Vision, Graphics, and Image Processing, vol. 23, 1983, pp. 128, 113. [2] S. Gull and G. Daniell, “Image reconstruction from incomplete and noisy data,” Nature, vol. 272, Apr. 1978, pp. 686-690.

  4. Research Idea • Classical image restoration methods can be exploited to do calibration in wireless sensor networks. • The methods are effective for both blind and non-blind calibration.

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