Spatial filter

About: Spatial filter is a research topic. Over the lifetime, 6170 publications have been published within this topic receiving 100451 citations.

Adaptive-neighborhood speckle removal in multitemporal synthetic aperture radar images.

Abstract: We present a new method for multitemporal synthetic aperture radar image filtering using three-dimensional (3D) adaptive neighborhoods. The method takes both spatial and temporal information into account to derive the speckle-free value of a pixel. For each pixel individually, a 3D adaptive neighborhood is determined that contains only pixels belonging to the same distribution as the current pixel. Then statistics computed inside the established neighborhood are used to derive the filter output. It is shown that the method provides good results by drastically reducing speckle over homogeneous areas while retaining edges and thin structures. The performances of the proposed method are compared in terms of subjective and objective measures with those given by several classical speckle-filtering methods.

Array mode selection utilizing an external cavity configuration

Abstract: We report operation of a ten‐stripe, gain‐guided, phase‐locked diode laser in an external cavity configuration. The laser radiates in a single narrow (1°) lobe. Such lasers generally lase in the highest order array mode, L=10, which radiates in a twin‐lobe far‐field pattern. With one antireflection‐coated facet and a slit spatial filter, the laser has been operated in the L=1, 2, 3 or 10 array modes. A theoretical explanation of the spatial filter function is included.

Computing illumination-invariant descriptors of spatially filtered color image regions

Abstract: Spatial filters provide a useful and efficient means of analyzing an input color image into components that capture different spatial properties. Representations based on spatial filtering have restricted usefulness for recognition, however, because the output of a spatial filter across an image depends on the scene illumination conditions. We use a physically accurate linear model for spectral reflectance to derive invariants of distributions in spatially filtered color images that do not depend on the scene illumination. These invariants can be used for the illumination-invariant recognition of regions following an arbitrary linear filtering operation. We describe a method for illumination correction based on color distributions and introduce an illumination change consistency constraint that is useful for verifying matches obtained using the invariants. We show, using a set of classification experiments, that the filtered distribution invariants can significantly improve the capability of a recognition system in environments where illumination cannot be controlled.

Flattening of the spatial laser beam profile with low losses and minimal beam divergence

Abstract: A new type of Nd:YAG laser is described that uses two spatial filters that are placed against the mirrors in the focal planes of a converging lens (Fourier planes). With the appropriate filters, we experimentally obtained a uniphase beam with a flat spatial profile and minimal beam divergence in the free-running regime.

Enhanced reflectivity contrast in confocal solid immersion lens microscopy

Abstract: The reflected image of a diffraction limited focused spot is investigated using confocal solid immersion microscopy. We find that the spot’s image shows aberrations when reflected off objects with optical indexes lower than that of the solid immersion lens (SIL) material. We demonstrate that such aberrations are only apparent and that the actual size of the spot at the SIL/object interface remains diffraction limited. The aberrations are due to lateral waves at the SIL surface. These von Schmidt waves originate from the total internal reflected components of a diverging spherical wave front. We make use of this image aberration in conjunction with the spatial filtering inherent to confocal microscopy in order to dramatically enhance the optical contrast of objects with low optical indexes.