New PDF release: Advanced Concepts for Intelligent Vision Systems: 8th

By Chul Keun Kim, Doug Young Suh, Gwang Hoon Park (auth.), Jacques Blanc-Talon, Wilfried Philips, Dan Popescu, Paul Scheunders (eds.)

ISBN-10: 3540446303

ISBN-13: 9783540446309

This ebook constitutes the refereed complaints of the eighth foreign convention on complicated ideas for clever imaginative and prescient structures, ACIVS 2006, held in Antwerp, Belgium in September 2006.

The forty five revised complete papers and sixty five revised poster papers offered have been conscientiously reviewed and chosen from round 242 submissions. The papers are geared up in topical sections on noise aid and recovery, segmentation, movement estimation and monitoring, video processing and coding, digicam calibration, snapshot registration and stereo matching, biometrics and safeguard, scientific imaging, picture retrieval and picture realizing, in addition to type and recognition.

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Read Online or Download Advanced Concepts for Intelligent Vision Systems: 8th International Conference, ACIVS 2006, Antwerp, Belgium, September 18-21, 2006. Proceedings PDF

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Extra resources for Advanced Concepts for Intelligent Vision Systems: 8th International Conference, ACIVS 2006, Antwerp, Belgium, September 18-21, 2006. Proceedings

Sample text

This paper deals with concealment of motion blur in image sequences. The approach is different from traditional methods, which attempt to deblur the image. Our approach utilizes the information in consecutive frames, replacing blurred areas of the images with corresponding sharp areas from the previous frames. Blurred but otherwise unchanged areas of the images are recognized using blur invariant features. A statistical approach for calculating the weights for the blur invariant features in frequency and spatial domains is also proposed, and compared to the unweighted invariants in an ideal setting.

Stiles, Color Science. O. fi Abstract. This paper deals with concealment of motion blur in image sequences. The approach is different from traditional methods, which attempt to deblur the image. Our approach utilizes the information in consecutive frames, replacing blurred areas of the images with corresponding sharp areas from the previous frames. Blurred but otherwise unchanged areas of the images are recognized using blur invariant features. A statistical approach for calculating the weights for the blur invariant features in frequency and spatial domains is also proposed, and compared to the unweighted invariants in an ideal setting.

We have used a redundant wavelet transform with the Haar wavelet and four resolution scales and a neighbourhood of size 9 × 9 (K = 4) for both the probabilistic version and the proposed one. As a measure of objective dissimilarity between a filtered image F and the original noisefree one O, we use the peak signal to noise ratio (PSNR). In order to get a clear idea of the performance of all mentioned methods we have carried out experiments for three well known test images: ‘Lena’, ‘Peppers’ and ‘Barbara’, each of size 512 × 512.

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Advanced Concepts for Intelligent Vision Systems: 8th International Conference, ACIVS 2006, Antwerp, Belgium, September 18-21, 2006. Proceedings by Chul Keun Kim, Doug Young Suh, Gwang Hoon Park (auth.), Jacques Blanc-Talon, Wilfried Philips, Dan Popescu, Paul Scheunders (eds.)


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