Sentence examples for loss of edge from inspiring English sources

Discusses "loss of edge".

Bliss doesn't have to mean a loss of edge.

By directly using the panoramic image, there is a loss of edge information and the appearance of false edges when applying the original Canny operator if the threshold values are constant throughout the entire panoramic image [29].

As mentioned in Section 4.4, the transmission map usually experiences a loss of edge information when estimation due to the primary operation of the bright/dark channel prior depends on the maximum/minimum filter.

In [12], Didas et al. combined ℓ2 data and gradient fitting in conjunction with ℓ1 regularization for image denoising, where the gradient fidelity term is used to compensate for the loss of edge and undesirable staircase effect introduced by the resulting higher partial differential equation.

However, though the transmission map is roughly good, there remains obvious block effects in some regions due to the primary operation of the dark channel prior depends on the minimum filter; the transmission map will usually experience a loss of edge information during estimation.

The results show that our proposed method has better denoising performance than the edge-sensitive filter, without any loss of edges.

The two algorithms reveal the details of the original image as well as minimize the loss of the edge sharpness in the nonuniform and low lighting conditions.

We calculated landscape metrics (habitat loss, amount of edge, patch shape complexity, and mean patch size) to identify the aspect of landscape transformation most captured by well density.

This works as an accumulator of gradient values of two difference image edge maps and reduces the loss of moving edge information on DT image due to overlapping of moving objects in the consecutive frames.

The optimal event and child mapping under s and is determined by minimizing the cost of the candidate solution at g: (5) where, the number of losses on edge (g, c i), is calculated using the loss heuristic in (Vernot et al., 2008).