Sentence examples for blurred estimates from inspiring English sources

In general, spatial EC approach produces blurred estimates of the lost MB as shown in Figure 5a, while the temporal EC approach produces edge artifacts as shown in Figure 5b, if the guessed MV is not accurate.

The system spatial resolution was calculated as where s is the manufacturer-characterized spot size measured per the British Standard Method [ 17] and d ≈ 33 μm is the spatial detector blur estimated from a measured edge-spread function.

By analyzing the observed blurred image it is possible to come up with more informative initial blur estimates; however in this study our focus is to develop a completely automated algorithm once the blur support is provided.

This iterative process is repeated until the algorithm converges and image and blur estimates are obtained at their native resolutions.

To avoid unrealistic blur estimates we adopt here a multi-scale scheme similar in spirit to the one proposed in [12].

After convergence is achieved at each scale we up-sample the image and the blur estimates to the next higher resolution and re-run the proposed algorithm.

Alternatively, the authors in [13, 14] introduced heuristic re-weighting of the regularization parameters, at each iteration, to prevent the algorithms from converging to unrealistic blur estimates.

After each iteration, we enforce the following constraints on the blur estimates: the positivity (blur elements less than zero are set to zero), the support constraint (blur elements outside of the blur support estimate are set to zero), and the energy conservation (sum of the blur elements equals one).

Specifically, more weighting is given to the local blur estimates that belong to salient regions of an image, while spatial blur values are pooled together to compute an overall value of blur for the whole image.

Additionally, the proposed multi-scale approach allows user to automatically initialize the proposed algorithm without visually inspecting the observed blurred image for determining the initial blur estimate.

In this paper, we present a novel motion tracking method with explicit modeling of motion blur, estimating the continuous motion of a rigid 3-D object with known geometry in a monocular video as well as the sharp object texture.