Narrow Results

Inspite of technological advancement, inherent processing capability of current age sensors limits the desired details in the acquired image for variety of remote sensing applications. Pan-sharpening is a prominent scheme to integrate the essential spatial details inferred from panchromatic (PAN) image and the desired spectral information of multispectral (MS) image. This paper presents an effective two-stage pan-sharpening method to produce high resolution multispectral (HRMS) image. The proposed method is based on the premise that the HRMS image can be formulated as an amalgam of spectral and spatial components. The spectral components are estimated by processing the interpolated MS image with a filter approximated with modulation transfer function (MTF) of the sensor. Sparse representation theory is adapted to construct the spatial components. The high-frequency details extracted from the PAN image and its low resolution variant are utilized to construct dual dictionaries. The dictionaries are jointly learned by an efficient training algorithm to enhance the adaptability. The hypothesis of sparse coefficients invariance over scales is also incorporated to reckon the appropriate spatial information. Further, an iterative filtering mechanism is developed to enhance the quality of fused image. Four distinct datasets generated from QuickBird, IKONOS, Pléiades and WorldView-2 sensors are used for experimentation. The comprehensive assessment at reduced-scale and full-scale persuade the effectiveness of proposed method in the retention of spectral information and intensification of the spatial details.

A one-dimensional (1D) point process, if considered as a random measure, can be represented by a sum, at most countable, of Delta Dirac measures concentrated at some random points. The integration with respect to the point process leads to the definition of the continuous wavelet transform of the process itself. As a possible choice of the mother wavelet, we propose the Mexican hat and the Morlet wavelet in order to implement the energy density of the process as a function of two wavelet parameters. Such mathematical tool works as a microscope to process an in-depth analysis of some classes of processes, in particular homogeneous, cluster, and locally scaled processes.

We show that the non-Machian feature of singularity in the General Theory of Relativity (GTR) can be avoided with scale-invariance. Further, the global non-conservation of energy in GTR results from inconsistency between scale-invariance and equivalence principle. We propose a negative energy density component with a positive equation of state that can drive the late-time acceleration in the universe, while the positive component confines to smaller scales.

A third regime is proposed in the natural progression of the description of the physical world - Classical to Quantum to Unified Field (U_F) Mechanics. We describe the new conceptual panoply and propose an experimental method to falsify the new U_F hypotheses. Like Penzias & Wilson wondering if bird droppings affected their antenna we describe a serendipitous insight into wavepacket dispersion of 1800 MHz telecommunication em-waves in the arena where signal strength attenuates periodically by factors attributed to perceived properties that we postulate can only be mediated by U_F mechanics. Salient suggested elements include extended geometrodynamics (duality of Newton’s instantaneous and Einstein’s relativistic models), Solar dynamo activity, geomagnetic phenomena, seasonal precession of the Earth’s axis, near - far field: geomagnetic core dynamo - solar scale-invariant wavepacket dispersion coupling and longitudinal em components. This U_F model putatively also provides an indirect measure of photon mass.

As our knowledge of reductionist details of living systems continues to grow, the gap in understanding life and consciousness remains wide. Progress has been made, e.g., biological organisms are seen as complex hierarchical amalgamations of elements interacting in self-similar, “scaleinvariant” patterns within and across spatio-temporal scales (“1/f”). But the mechanism for trans-scalar communication is unknown, as are the origin and foundation, i.e., the “bottom floor” of scale-invariant systems in biology. Here, we describe scale-invariant hierarchies in brain and living organisms in general, originating in a biomolecular “quantum underground” pervading neurons, glia and all living cells, most specifically within cytoskeletal microtubules. The quantum underground is a non-polar solubility phase composed largely of π-electron resonance clouds of aromatic amino acids, similar to pi-resonance arrays mediating quantum coherence in photosynthesis proteins. In the brain, the quantum underground is identified as the origin of consciousness by the Meyer-Overton correlation, showing where anesthetics act to erase consciousness while sparing non-conscious brain activities. Evidence points to anesthetics acting to dampen quantum dipole oscillations in the “Meyer-Overton quantum underground” within brain neuronal microtubules. These quantum dipole oscillations are seen as the “inward apex,” the origin of scale-invariant processes in consciousness and life.