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Plano, TX, United States

Sabir M.F.,Vucomp Inc. | Bovik A.C.,University of Texas at Austin | Heath Jr. R.W.,University of Texas at Austin
IEEE Transactions on Image Processing | Year: 2010

With the introduction of multiple transmit and receive antennas in next generation wireless systems, real-time image and video communication are expected to become quite common, since very high data rates will become available along with improved data reliability. New joint transmission and coding schemes that explore advantages of multiple antenna systems matched with source statistics are expected to be developed. Based on this idea, we present an unequal power allocation scheme for transmission of JPEG compressed images over multiple-input multiple-output systems employing spatial multiplexing. The JPEG-compressed image is divided into different quality layers, and different layers are transmitted simultaneously from different transmit antennas using unequal transmit power, with a constraint on the total transmit power during any symbol period. Results show that our unequal power allocation scheme provides significant image quality improvement as compared to different equal power allocations schemes, with the peak-signal-to-noise-ratio gain as high as 14 dB at low signal-to-noise-ratios. © 2010 IEEE. Source

Vucomp Inc. | Date: 2011-06-24

An image segmentation embodiment comprises generating a start model comprising a set of model points approximating an outline of an object in an initial image, smoothing the image at a first smoothing level, generating a curvature image by applying a second derivative operator, locating second derivative local maxima in the curvature image that are orthogonal to a respective model point and within a search region having a first boundary on one side of the start model and a second boundary on an opposite side of the start model, generating a set of contours, shifting the start model to an outer boundary of the contours, and generating a segmentation mask of the object based on the shifted start model.

Vucomp Inc. | Date: 2011-06-24

An image segmentation embodiment comprises applying a second derivative operator to the pixels of an image, growing a set of contours using seeding grid points as potential contour starting points, determining a contour strength vector for each of the contour pixels, generating a partial ellipse representing an estimated location of an object in the image, dividing the partial ellipse into a plurality of support sectors with control points, determining a contour strength and position for each contour, adjusting a position of each sector control point based on the contour positions weighted by the contour strengths of the contours centered in the respective sector, fitting the partial ellipse to the adjusted positions of the control points, and generating a segmentation mask of the object based on the partial fitted ellipse.

An embodiment method for marking an anomaly in an image comprises generating an initial boundary description representing a size, a shape and a location of the anomaly in the image, dilating the initial boundary description to generate a dilated boundary description representing the shape, the location and an enlarged size of the initial boundary description, and saving, on a non-transitory computer-readable medium, the dilated boundary description as an overlay plane object in an output format compliant with a industry standard digital image format.

An analysis of a digitized image is provided. The digitized image is repeatedly convolved to form first convolved images, which first convolved images are convolved a second time to form second convolved images. Each first convolved image and the respective second convolved image representing a stage, and each stage represents a different scale or size of anomaly. As an example, the first convolution may utilize a Gaussian convolver, and the second convolution may utilize a Laplacian convolver, but other convolvers may be used. The second convolved image from a current stage and the first convolved image from a previous stage are used with a neighborhood median determined from the second convolved image from the current stage by a peak detector to detect peaks, or possible anomalies for that particular scale.

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