Sentence examples for knowledge of the image from inspiring English sources

We develop a corresponding sampling design methodology that deterministically yields a near optimal sampling distribution for image reconstructions incorporating knowledge of the image geometry.

Automatically evaluating the compliance of a face image to such requirements needs a precise knowledge of the image structure, intended as the partitioning of the image into its main components (face, hair, clothes and background regions).

When prior knowledge of the image geometry is available as a binarized image, such as for microfluidic MRI, it is possible to reduce sampling requirements by incorporating this information into the reconstruction algorithm.

The technique robustly identifies optimal weighted random sampling schemes and provides improved reconstruction fidelity for multiple 1D and 2D images, when compared to prior techniques for sampling optimization given knowledge of the image geometry.

This work explores the tradeoff between signal acquisition and incoherent sampling on image reconstruction quality given prior knowledge of the image geometry for weighted random sampling schemes, finding that optimal distribution is not robustly determined by maximizing the acquired signal but from interpreting its marginal change with respect to the sub-sampling rate.

This method is independent of features, categories, or other prior knowledge of the image.

The challenge of such an approach, however, would be in finding the disparity information without prior knowledge of the images themselves.

No-reference/blind image quality assessment (BIQA) is designed to measure the image quality without any knowledge of the reference image.

Further­ more, knowledge of how the image is produced helps in appreciating the ori­ gin of the artifacts sometimes found in MRI due to effects like patient motion and fluid flow.

It uses the knowledge of the preceding image as a prior to predict the present functional MR image, and the observations are used to modify the prediction.

To the best of our knowledge, none of the image analysis software packages available to date provide the tools necessary test for the distribution of the data.