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Let be the floating image and be the reference image defined on a continuous domain.
We consider the disparity map with respect to IL, which is taken to be the reference image.
In this method, the last (i.e., most recent) observed LR frame is considered to be the reference image, denoted as r.
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The floating image was then registered to the other image which was the reference image.
Suppose that the image with shorter exposure is the reference image.
(a) is the reference image to which all images are registered.
At this point, the controversial issue is the reference image selection, I.
The inputs to the framework are the reference image Ir and the images captured with different cameras, called test images It.
where n is the number of images; x i is the current image; r i is the reference image or location measure; f is the number of features; i is the feature column of image.
The second (G 1,27) is the reference image produced by individual 1. Between the output image evaluated and its reference image in the G T 1 set, there is a uniformity discrepancy on the edge of the segmented region, especially the top and bottom extremities.
It should be noted that the two input images can be either two unregistered images or two images that have been previously registered, while one is the reference image and the other is the transformed image.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com