It has been an important approach of using matrix completion to perform image restoration. Most previous works on focus the low-rank property by imposing explicit constraints recovered matrix, such as constraint nuclear norm or limiting dimension factorization component. Recently, theoretical suggest that deep linear neural network implicit bias towards low rank completion. However, is not adeq...

We consider two complementary operations: Hairpin completion introduced in [D. Cheptea, C. Martin-Vide, V. Mitrana, A new operation on words suggested by DNA biochemistry: Hairpin completion, in: Proc. Transgressive Computing, 2006, pp. 216–228] with motivations coming from DNA biochemistry and hairpin reduction as the inverse operation of the hairpin completion. Both operations are viewed here...

We describe a local parallel method for computing the stochastic completion field introduced in the previous article (Williams and Jacobs, 1997). The stochastic completion field represents the likelihood that a completion joining two contour fragments passes through any given position and orientation in the image plane. It is based on the assumption that the prior probability distribution of co...

To suitably complete an image without seams, block effects, and artifacts, a novel exemplar-based image completion model employing partial differential equation (PDE) is proposed. Firstly, the novel model determines the processing order of exemplar according to a composite function, which is the product of the colour property and structure property in exemplar. Then the exemplar along a geometr...

When one monocular image contains a red square partly occluding a green square, and the other monocular image is the same except that the green square is partly occluding the red one, the two images resemble each other's amodal completion. Observers typically perceive two complete squares as if the red and green surfaces are transparent or penetrating each other at their overlapping image locat...