The Experts below are selected from a list of 4251 Experts worldwide ranked by ideXlab platform
Kwan Y. Wong - One of the best experts on this subject based on the ideXlab platform.
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ICRA - Imaging system response linearization and shading correction
Proceedings. 1984 IEEE International Conference on Robotics and Automation, 1Co-Authors: Its'hak Dinstein, Fritz Merkle, Tinwai D. Lam, Kwan Y. WongAbstract:Shading correction of image sensors is a very important operation in visual inspection applications. The generation and application of shading correction with and without imaging system response linearization is discussed and demonstrated. The linearization is achieved by subtracting the dark current image and by applying a lookup table operation. The content of the lookup table is obtained by fitting an analytical function to the measured system response. The linearization enables the shading correction to be a linear operation. The quality of the linearization and the shading correction was evaluated using statistical parameters of the processed images. The results showed a substantial decrease in the standard deviation of the Gray Level Distribution of uniform reference images.
Its'hak Dinstein - One of the best experts on this subject based on the ideXlab platform.
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ICRA - Imaging system response linearization and shading correction
Proceedings. 1984 IEEE International Conference on Robotics and Automation, 1Co-Authors: Its'hak Dinstein, Fritz Merkle, Tinwai D. Lam, Kwan Y. WongAbstract:Shading correction of image sensors is a very important operation in visual inspection applications. The generation and application of shading correction with and without imaging system response linearization is discussed and demonstrated. The linearization is achieved by subtracting the dark current image and by applying a lookup table operation. The content of the lookup table is obtained by fitting an analytical function to the measured system response. The linearization enables the shading correction to be a linear operation. The quality of the linearization and the shading correction was evaluated using statistical parameters of the processed images. The results showed a substantial decrease in the standard deviation of the Gray Level Distribution of uniform reference images.
Fritz Merkle - One of the best experts on this subject based on the ideXlab platform.
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ICRA - Imaging system response linearization and shading correction
Proceedings. 1984 IEEE International Conference on Robotics and Automation, 1Co-Authors: Its'hak Dinstein, Fritz Merkle, Tinwai D. Lam, Kwan Y. WongAbstract:Shading correction of image sensors is a very important operation in visual inspection applications. The generation and application of shading correction with and without imaging system response linearization is discussed and demonstrated. The linearization is achieved by subtracting the dark current image and by applying a lookup table operation. The content of the lookup table is obtained by fitting an analytical function to the measured system response. The linearization enables the shading correction to be a linear operation. The quality of the linearization and the shading correction was evaluated using statistical parameters of the processed images. The results showed a substantial decrease in the standard deviation of the Gray Level Distribution of uniform reference images.
Tinwai D. Lam - One of the best experts on this subject based on the ideXlab platform.
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ICRA - Imaging system response linearization and shading correction
Proceedings. 1984 IEEE International Conference on Robotics and Automation, 1Co-Authors: Its'hak Dinstein, Fritz Merkle, Tinwai D. Lam, Kwan Y. WongAbstract:Shading correction of image sensors is a very important operation in visual inspection applications. The generation and application of shading correction with and without imaging system response linearization is discussed and demonstrated. The linearization is achieved by subtracting the dark current image and by applying a lookup table operation. The content of the lookup table is obtained by fitting an analytical function to the measured system response. The linearization enables the shading correction to be a linear operation. The quality of the linearization and the shading correction was evaluated using statistical parameters of the processed images. The results showed a substantial decrease in the standard deviation of the Gray Level Distribution of uniform reference images.
Guy Cloutier - One of the best experts on this subject based on the ideXlab platform.
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Intravascular ultrasound image segmentation: a three-dimensional fast-marching method based on Gray Level Distributions
IEEE transactions on medical imaging, 2006Co-Authors: Marie-hélène Roy Cardinal, Jean Meunier, Gilles Soulez, Roch L. Maurice, Eric Therasse, Guy CloutierAbstract:Intravascular ultrasound (IVUS) is a catheter based medical imaging technique particularly useful for studying atherosclerotic disease. It produces cross-sectional images of blood vessels that provide quantitative assessment of the vascular wall, information about the nature of atherosclerotic lesions as well as plaque shape and size. Automatic processing of large IVUS data sets represents an important challenge due to ultrasound speckle, catheter artifacts or calcification shadows. A new three-dimensional (3-D) IVUS segmentation model, that is based on the fast-marching method and uses Gray Level probability density functions (PDFs) of the vessel wall structures, was developed. The Gray Level Distribution of the whole IVUS pullback was modeled with a mixture of Rayleigh PDFs. With multiple interface fast-marching segmentation, the lumen, intima plus plaque structure, and media layers of the vessel wall were computed simultaneously. The PDF-based fast-marching was applied to 9 in vivo IVUS pullbacks of superficial femoral arteries and to a simulated IVUS pullback. Accurate results were obtained on simulated data with average point to point distances between detected vessel wall borders and ground truth
