Efficient motion blur parameters estimation under noisy conditions
| Autor: | Saurabh Mishra, R. K. Puri, Ratnesh Singh Sengar, D. N. Badodkar |
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| Rok vydání: | 2014 |
| Předmět: |
Radon transform
Noise measurement business.industry Computer science Motion blur ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Gaussian blur Image processing symbols.namesake Gaussian noise Computer Science::Computer Vision and Pattern Recognition symbols Computer vision Artificial intelligence business Bispectrum Image restoration ComputingMethodologies_COMPUTERGRAPHICS |
| Zdroj: | 2014 IEEE International Conference on Computational Intelligence and Computing Research. |
| Popis: | Image restoration of noisy motion blurred images is a challenging problem in image processing. The quality of restoration of such images depends on the perfect estimation of blur parameters. In this paper, an algorithm is proposed to estimate linear motion blur parameters such as blur length and motion direction under noisy conditions. In the proposed algorithm, pre-processing of the noisy image requires appropriate windowing and subsequently dual Fourier transform of the image. Blur angle is estimated accurately using Radon Transform on a specific bit plane image of the dual Fourier transformed image. For accurate estimation of blur length in presence of noise, the image is processed in bispectrum domain as the bispectrum suppresses additive Gaussian noise. A robust novel exponential model is proposed based on curve fitting that represents the behavior of blur length in bispectrum domain. The maximum error in the estimated blur angle and the blur length is less than 1.6° and 2 pixels respectively in presence of additive Gaussian noise of variance up to 150. Experimental results are also compared with the previous methods to demonstrate the superior performance of the proposed algorithm. |
| Databáze: | OpenAIRE |
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