Abstract: A method and system for detecting vulnerable wireless networks coexisting in a wireless environment of an organization are provided. The method includes receiving intercepted traffic, wherein the intercepted traffic is transmitted by at least one wireless device operable in an airspace of the wireless environment, wherein the intercepted traffic is transported using at least one type of wireless protocol; analyzing the received traffic to detect at least one active connection between a legitimate wireless device of the at least one wireless device and at least one unknown wireless device, wherein the legitimate wireless device is at least legitimately authorized to access a protected computing resource of the organization; and determining if the at least one detected active connection forms a vulnerable wireless network.

Abstract: Several autofocus techniques are disclosed. The autofocus techniques help the device to achieve focus without presenting unpleasant blurred images to the operator of the camera, e.g., by dividing image frames into technical frames and display frames, with autofocus search occurring during technical frames. With another technique, the upper bound of the spatial frequencies of the blurred image permits a calculation of the focused lens position. Another technique searches for focus in jumps that exponentially decrease the search space with each jump. In another focusing technique, the lens is moved through a range of positions during a frame acquired with a rolling shutter exposure and the focused position may be determined from the sharpest row of the frame.

Abstract: A 9 pixel-by-9 pixel working window slides over an input Bayer image. For each such window, a demosaicing operation is performed. For each such window, corrective processing is performed relative to that window to produce relative differences for that window. For each such window for which relative differences have been produced, those relative differences are regulated. For each window, a maximum is found for that window's regulated relative differences; in one embodiment of the invention, this maximum is used to select which channel is sharp. For each window, the colors in that window are corrected based on the relative difference-based maximum found for that window. For each window, edge oversharpening is softened in order to avoid artifacts in the output image. The result is an output image in which axial chromatic aberrations have been corrected.

Abstract: A chromatic noise reduction method is provided for removing chromatic noise from the pixels of a mosaic image. In one implementation, an actual chroma value and a de-noised chroma value are derived for the central pixel of a matrix of pixels. Based at least in part upon these chroma values, a final chroma value is derived for the central pixel. The final chroma value is then used, along with the actual luminance of the central pixel, to derive a final de-noised pixel value for the central pixel. By de-noising the central pixel based on its chroma (which takes into account more than one color) rather than on just the color channel of the central pixel, this method allows the central pixel to be de-noised in a more color-coordinated fashion. As a result, improved chromatic noise reduction is achieved.

Abstract: A 9 pixel-by-9 pixel working window slides over an input Bayer image. For each such window, a demosaicing operation is performed. For each such window, corrective processing is performed relative to that window to produce relative differences for that window. For each such window for which relative differences have been produced, those relative differences are regulated. For each window, a maximum is found for that window's regulated relative differences; in one embodiment of the invention, this maximum is used to select which channel is sharp. For each window, the colors in that window are corrected based on the relative difference-based maximum found for that window. For each window, edge oversharpening is softened in order to avoid artifacts in the output image. The result is an output image in which axial chromatic aberrations have been corrected.

Abstract: A technique is disclosed for calculating a value for a second color for a particular pixel. The technique selects a first set of neighboring pixels situated on a first side of the particular pixel, and a second set of neighboring pixels situated on an opposite side of the particular pixel. Based upon color values from the first set of neighboring pixels, the technique determines a first representative relationship, and based upon color values from the second set of neighboring pixels, the technique determines a second representative relationship. Based upon these representative relationships, the technique determines a target relationship between the value for the second color for the particular pixel and a value for a first color for the particular pixel. Based upon the target relationship and the value for the first color for the particular pixel, the technique calculates the value for the second color for the particular pixel.

Abstract: A chromatic noise reduction method is provided for removing chromatic noise from the pixels of a mosaic image. In one implementation, an actual chroma value and a de-noised chroma value are derived for the central pixel of a matrix of pixels. Based at least in part upon these chroma values, a final chroma value is derived for the central pixel. The final chroma value is then used, along with the actual luminance of the central pixel, to derive a final de-noised pixel value for the central pixel. By de-noising the central pixel based on its chroma (which takes into account more than one color) rather than on just the color channel of the central pixel, this method allows the central pixel to be de-noised in a more color-coordinated fashion. As a result, improved chromatic noise reduction is achieved.

Abstract: A technique is disclosed for calculating a value for a second color for a particular pixel. The technique selects a first set of neighboring pixels situated on a first side of the particular pixel, and a second set of neighboring pixels situated on an opposite side of the particular pixel. Based upon color values from the first set of neighboring pixels, the technique determines a first representative relationship, and based upon color values from the second set of neighboring pixels, the technique determines a second representative relationship. Based upon these representative relationships, the technique determines a target relationship between the value for the second color for the particular pixel and a value for a first color for the particular pixel. Based upon the target relationship and the value for the first color for the particular pixel, the technique calculates the value for the second color for the particular pixel.

Abstract: A method for a chromatic adaptation transformation of images using temperature and tint space comprises the steps of: acquiring a red, green, blue (RGB) image using a camera (11); providing neutral RGB values for camera specific, and at least one of a selected highlight and shadow values, to produce a 3D lookup transformation table (21); calibrating the RGB image by applying the 3D lookup transformation table to produce a calibrated RGB image (22); calculating a Von Kries transform from specific temperature and tint values (14); and applying a chromatic adaptation to the calibrated RGB image using the Von Kries transform to produce a modified RGB image chromatically adapted (15), while maintaining neutral RGB values for highlight and shadow regions.

Abstract: A method for a chromatic adaptation transformation of images using temperature and tint space comprises the steps of: acquiring a red, green, blue (RGB) image using a camera (11); providing neutral RGB values for camera specific, and at least one of a selected highlight and shadow values, to produce a 3D lookup transformation table (21); calibrating the RGB image by applying the 3D lookup transformation table to produce a calibrated RGB image (22); calculating a Von Kries transform from specific temperature and tint values (14); and applying a chromatic adaptation to the calibrated RGB image using the Von Kries transform to produce a modified RGB image chromatically adapted (15), while maintaining neutral RGB values for highlight and shadow regions.