Fusion of infrared polarization and intensity images using support value transform and fuzzy combination rules

Infrared polarization and intensity imagery provide complementary and discriminative information in image understanding and interpretation. In this paper, a novel fusion method is proposed by effectively merging the information with various combination rules. It makes use of both low-frequency and highfrequency images components from support value transform (SVT), and applies fuzzy logic in the combination process. Images (both infrared polarization and intensity images) to be fused are firstly decomposed into low-frequency component images and support value image sequences by the SVT. Then the low-frequency component images are combined using a fuzzy combination rule blending three sub-combination methods of (1) region feature maximum, (2) region feature weighting average, and (3) pixel value maximum; and the support value image sequences are merged using a fuzzy combination rule fusing two sub-combination methods of (1) pixel energy maximum and (2) region feature weighting. With the variables of two newly defined features, i.e. the low-frequency difference feature for low-frequency component images and the support-value difference feature for support value image sequences, trapezoidal membership functions are proposed and developed in tuning the fuzzy fusion process. Finally the fused image is obtained by inverse SVT operations. Experimental results of visual inspection and quantitative evaluation both indicate the superiority of the proposed method to its counterparts in image fusion of infrared polarization and intensity images.

The role of the harmonic vector average in motion integration

The local speeds of object contours vary systematically with the cosine of the angle between the normal component of the local velocity and the global object motion direction. An array of Gabor elements whose speed changes with local spatial orientation in accordance with this pattern can appear to move as a single surface. The apparent direction of motion of plaids and Gabor arrays has variously been proposed to result from feature tracking, vector addition and vector averaging in addition to the geometrically correct global velocity as indicated by the intersection of constraints (IOC) solution. Here a new combination rule, the harmonic vector average (HVA), is introduced, as well as a new algorithm for computing the IOC solution. The vector sum can be discounted as an integration strategy as it increases with the number of elements. The vector average over local vectors that vary in direction always provides an underestimate of the true global speed. The HVA, however, provides the correct global speed and direction for an unbiased sample of local velocities with respect to the global motion direction, as is the case for a simple closed contour. The HVA over biased samples provides an aggregate velocity estimate that can still be combined through an IOC computation to give an accurate estimate of the global velocity, which is not true of the vector average. Psychophysical results for type II Gabor arrays show perceived direction and speed falls close to the IOC direction for Gabor arrays having a wide range of orientations but the IOC prediction fails as the mean orientation shifts away from the global motion direction and the orientation range narrows. In this case perceived velocity generally defaults to the HVA.

Cue combination for 3D location judgements

Cue combination rules have often been applied to the perception of surface shape but not to judgements of object location. Here, we used immersive virtual reality to explore the relationship between different cues to distance. Participants viewed a virtual scene and judged the change in distance of an object presented in two intervals, where the scene changed in size between intervals (by a factor of between 0.25 and 4). We measured thresholds for detecting a change in object distance when there were only 'physical' (stereo and motion parallax) or 'texture-based' cues (independent of the scale of the scene) and used these to predict biases in a distance matching task. Under a range of conditions, in which the viewing distance and position of the tarte relative to other objects was varied, the ration of 'physical' to 'texture-based' thresholds was a good predictor of biases in the distance matching task. The cue combination approach, which successfully accounts for our data, relies on quite different principles from those underlying geometric reconstruction.

Ex Vivo Construction of an Artificial Ocular Surface by Combination of Corneal Limbal Epithelial Cells and a Compressed Collagen Scaffold Containing Keratocytes

We have investigated the use of a laminin coated compressed collagen gel containing corneal fibroblasts (keratocytes) as a novel scaffold to support the growth of corneal limbal epithelial stem cells. The growth of limbal epithelial cells was compared between compressed collagen gel and a clinically proven conventional substrate, denuded amniotic membrane. Following compression of the collagen gel, encapsulated keratocytes remained viable and scanning electron microscopy showed that fibres within the compressed gel were dense, homogeneous and similar in structure to those within denuded amniotic membrane. Limbal epithelial cells were successfully expanded upon the compressed collagen resulting in stratified layers of cells containing desmosome and hemidesmosome structures. The resulting corneal constructs of both the groups shared a high degree of transparency, cell morphology and cell stratification. Similar protein expression profiles for cytokeratin 3 and cytokeratin 14 and no significant difference in cytokeratin 12 mRNA expression levels by real time PCR were also observed. This study provides the first line of evidence that a laminin coated compressed collagen gel containing keratocytes can adequately support limbal epithelial cell expansion, stratification and differentiation to a degree that is comparable to the leading conventional scaffold, denuded amniotic membrane.

Combination therapy: opportunities and challenges for polymer-drug conjugates as anticancer nanomedicines.

The discovery of new molecular targets and the subsequent development of novel anticancer agents are opening new possibilities for drug combination therapy as anticancer treatment. Polymer-drug conjugates are well established for the delivery of a single therapeutic agent, but only in very recent years their use has been extended to the delivery of multi-agent therapy. These early studies revealed the therapeutic potential of this application but raised new challenges (namely, drug loading and drugs ratio, characterisation, and development of suitable carriers) that need to be addressed for a successful optimisation of the system towards clinical applications.

Polymer-drug conjugates for combination anticancer therapy: investigating the mechanism of action.

We developed a family of polymer-drug conjugates carrying the combination of the anticancer agent epirubicin (EPI) and nitric oxide (NO). EPI-PEG-(NO)8, carrying the highest content of NO, displayed greater activity in Caco-2 cells while it decreased toxicity against endothelium cells and cardiomyocytes with respect to free EPI. FACS and confocal microscopy confirmed conjugates internalization. Light scattering showed formation of micelle whose size correlated with internalization rate. EPI-PEG-(NO)8 showed increased bioavailability in mice compared to free EPI.

Depth by The Rule

This note corrects a previous treatment of algorithms for the metric DTR, Depth by the Rule.