Variational models for color image correction inspired by visual perception and neuroscience

Reproducing the perception of a real-world scene on a display device is a very challenging task which requires the understanding of the camera processing pipeline, the display process, and the way the human visual system processes the light it captures. Mathematical models based on psychophysical and physiological laws on color vision, named Retinex, provide efficient tools to handle degradations produced during the camera processing pipeline like the reduction of the contrast. In particular, Batard and Bertalmío [J Math. Imag. Vis. 60(6), 849-881 (2018)] described some psy-chophysical laws on brightness perception as covariant derivatives, included them into a variational model, and observed that the quality of the color image correction is correlated with the accuracy of the vision model it includes. Based on this observation, we postulate that this model can be improved by including more accurate data on vision with a special attention on visual neuro-science here. Then, inspired by the presence of neurons responding to different visual attributes in the area V1 of the visual cortex as orientation, color or movement, to name a few, and horizontal connections modeling the interactions between those neurons, we construct two variational models to process both local (edges, textures) and global (contrast) features. This is an improvement with respect to the model of Batard and Bertalmío as the latter can not process local and global features independently and simultaneously. Finally, we conduct experiments on color images which corroborate the improvement provided by the new models

Topographical coloured plasmonic coins

The use of metal nanostructures for colourization has attracted a great deal of interest with the recent developments in plasmonics. However, the current top-down colourization methods based on plasmonic concepts are tedious and time consuming, and thus unviable for large-scale industrial applications. Here we show a bottom-up approach where, upon picosecond laser exposure, a full colour palette independent of viewing angle can be created on noble metals. We show that colours are related to a single laser processing parameter, the total accumulated fluence, which makes this process suitable for high throughput industrial applications. Statistical image analyses of the laser irradiated surfaces reveal various distributions of nanoparticle sizes which control colour. Quantitative comparisons between experiments and large-scale finite-difference time-domain computations, demonstrate that colours are produced by selective absorption phenomena in heterogeneous nanoclusters. Plasmonic cluster resonances are thus found to play the key role in colour formation.Comment: 9 pages, 5 figure

X-Ray Image Processing and Visualization for Remote Assistance of Airport Luggage Screeners

X-ray technology is widely used for airport luggage inspection nowadays. However, the ever-increasing sophistication of threat-concealment measures and types of threats, together with the natural complexity, inherent to the content of each individual luggage make x-ray raw images obtained directly from inspection systems unsuitable to clearly show various luggage and threat items, particularly low-density objects, which poses a great challenge for airport screeners. This thesis presents efforts spent in improving the rate of threat detection using image processing and visualization technologies. The principles of x-ray imaging for airport luggage inspection and the characteristics of single-energy and dual-energy x-ray data are first introduced. The image processing and visualization algorithms, selected and proposed for improving single energy and dual energy x-ray images, are then presented in four categories: (1) gray-level enhancement, (2) image segmentation, (3) pseudo coloring, and (4) image fusion. The major contributions of this research include identification of optimum combinations of common segmentation and enhancement methods, HSI based color-coding approaches and dual-energy image fusion algorithms —spatial information-based and wavelet-based image fusions. Experimental results generated with these image processing and visualization algorithms are shown and compared. Objective image quality measures are also explored in an effort to reduce the overhead of human subjective assessments and to provide more reliable evaluation results. Two application software are developed − an x-ray image processing application (XIP) and a wireless tablet PC-based remote supervision system (RSS). In XIP, we implemented in a user-friendly GUI the preceding image processing and visualization algorithms. In RSS, we ported available image processing and visualization methods to a wireless mobile supervisory station for screener assistance and supervision. Quantitative and on-site qualitative evaluations for various processed and fused x-ray luggage images demonstrate that using the proposed algorithms of image processing and visualization constitutes an effective and feasible means for improving airport luggage inspection