Perceptual restoration in toddlers

Perceptual regularization functionals for natural image restoration

Regularization constraints are necessary in inverse problems such as image restoration, optical flow computation or shape from shading to avoid the singularities in the solution. Conventional regularization techniques are based on some a priori knowledge of the solution: usually, the solution is assumed to be smooth according to simple statistical image or motion models. Using the fact that hum...

Perceptual restoration of masked speech in human cortex

Humans are adept at understanding speech despite the fact that our natural listening environment is often filled with interference. An example of this capacity is phoneme restoration, in which part of a word is completely replaced by noise, yet listeners report hearing the whole word. The neurological basis for this unconscious fill-in phenomenon is unknown, despite being a fundamental characte...

Developmental improvements in perceptual restoration : Can young children

Young children are frequently exposed to sounds such as speech and music in noisy listening conditions, which have the potential to disrupt their learning. Missing input that is masked by louder sounds can, under the right conditions, be ‘filled in’ by the perceptual system, using a process known as perceptual restoration. This experiment compared the ability of 4to 6-year old children, 9to 11-...

From Image Quality Assessment to Perceptual Quality Preserved Image Restoration: A Perceptual Transform Learning

Binary Partitioning, Perceptual Grouping, and Restoration with Semidefinite Programming1

We introduce a novel optimization method, semidefinite programming, to the field of computer vision and apply it to the combinatorial problem of minimizing quadratic functionals in binary decision variables subject to linear constraints. The approach is (tuning) parameter free and computes high-quality combinatorial solutions using interior-point methods (convex programming) and a randomized hy...