Linear demosaicing inspired by the human visual system.

There is an analogy between single-chip color cameras and the human visual system in that these two systems acquire only one limited wavelength sensitivity band per spatial location. We have exploited this analogy, defining a model that characterizes a one-color per spatial position image as a coding into luminance and chrominance of the corresponding three colors per spatial position image. Luminance is defined with full spatial resolution while chrominance contains subsampled opponent colors. Moreover, luminance and chrominance follow a particular arrangement in the Fourier domain, allowing for demosaicing by spatial frequency filtering. This model shows that visual artifacts after demosaicing are due to aliasing between luminance and chrominance and could be solved using a preprocessing filter. This approach also gives new insights for the representation of single-color per spatial location images and enables formal and controllable procedures to design demosaicing algorithms that perform well compared to concurrent approaches, as demonstrated by experiments.

Image phase or amplitude? Rapid scene categorization is an amplitude-based process.

Models of the visual cortex are based on image decomposition according to the Fourier spectrum (amplitude and phase). On one hand, it is commonly believed that phase information is necessary to identify a scene. On the other hand, it is known that complex cells of the visual cortex, the most numerous ones, code only the amplitude spectrum. This raises the question of knowing if these cells carry sufficient information to allow visual scene categorization. In this work, using the same experiments in computer simulation and in psychophysics, we provide arguments to show that the amplitude spectrum alone is sufficient for categorization task.