HOMPC: A Local Feature Descriptor Based on the Combination of Magnitude and Phase Congruency Information for Multi-Sensor Remote Sensing Images

Local region description of multi-sensor images remains a challenging task in remote sensing image analysis and applications due to the non-linear radiation variations between images. This paper presents a novel descriptor based on the combination of the magnitude and phase congruency information of local regions to capture the common features of images with non-linear radiation changes. We first propose oriented phase congruency maps (PCMs) and oriented magnitude binary maps (MBMs) using the multi-oriented phase congruency and magnitude information of log-Gabor filters. The two feature vectors are then quickly constructed based on the convolved PCMs and MBMs. Finally, a dense descriptor named the histograms of oriented magnitude and phase congruency (HOMPC) is developed by combining the histograms of oriented phase congruency (HPC) and the histograms of oriented magnitude (HOM) to capture the structure and shape properties of local regions. HOMPC was evaluated with three datasets composed of multi-sensor remote sensing images obtained from unmanned ground vehicle, unmanned aerial vehicle, and satellite platforms. The descriptor performance was evaluated by recall, precision, F1-measure, and area under the precision-recall curve. The experimental results showed the advantages of the HOM and HPC combination and confirmed that HOMPC is far superior to the current state-of-the-art local feature descriptors.

Evidence-based psychopharmacotherapy. A valid and reliable approach?

Summary Objective: Psychopharmacotherapy should now be regulated in the sense of evidence-based medicine (EBM), as is the case in other areas of clinical treatment in medicine. Methods: Descriptive overview of limitations and problems of EBM in pharmacopsychiatry. Results: In general this is a meaningful development, which principally will have a positive impact on routine health care in psychiatry. But several related problems should not be ignored. So far consensus on an internationally accepted evidence graduation could not be reached, due to several difficulties related to this. For example, to focus on the results of meta-analyses instead of considering relevant single studies results in a decision-making logic which is in conflict with the rationale applied by drug authorities in the licensing process. Attempts to regulate psychopharmacotherapy in the sense of EBM come closer to their limits the more complex the clinical situation and the respective decision-making logic are. Conclusion: EBM has severe problems and limitations. Even in times of EBM a large part of complex clinical decision-making in psychopharmacotherapy still relies more on clinical experience and a consensus about clinical experience, traditions and belief systems than on results of efficacy oriented phase-III and effectiveness-oriented phase-IV clinical studies.

A Two-Layer Model of Natural Stimuli Estimated with Score Matching

We consider a hierarchical two-layer model of natural signals in which both layers are learned from the data. Estimation is accomplished by score matching, a recently proposed estimation principle for energy-based models. If the first-layer outputs are squared and the second-layer weights are constrained to be nonnegative, the model learns responses similar to complex cells in primary visual cortex from natural images. The second layer pools a small number of features with similar orientation and frequency, but differing in spatial phase. For speech data, we obtain analogous results. The model unifies previous extensions to independent component analysis such as subspace and topographic models and provides new evidence that localized, oriented, phase-invariant features reflect the statistical properties of natural image patches.