Exelis Inc.

Kenneth Michael Brodeur

Theodore Anthony Tantalo

Eric August Woodward

Angela Marie D'Orazio

Timothy Paul Hahm

A method combines two digital images, one in the visible range and the other in the infrared range. The combined image provides an intensity band of pixels and shows detected warm objects that are superimposed on the intensity band of pixels. A user of the present invention may (1) view increased detail in the fused image of a scene and (2) have high confidence that an object in the scene is warm or hot. Hot objects collected by the infrared channel, but not visible in the visible channel may also be seen by the viewer in the fused image.

Smart fusion of visible and infrared image data

A system including a processor for adjusting the dynamic range of an image including a plurality of pixels. The processor segments the pixels into blocks, and computes statistical values for each block based on intensity values of the pixels. The processor also adjusts the dynamic range of the image by controlling the intensity values of the pixels based on the statistical values.

Spatially variant dynamic range adjustment for still frames and videos

A method for extracting a target from a series of images includes the steps of: (a) estimating an ambient temperature value of pixels in the series of images; (b) finding a band of pixel values having temperature values above the ambient temperature value, the band of pixel values forming a histogram; and (c) differentiating the histogram to estimate a threshold. Also included are steps (d) extracting the target having pixel values above the threshold; and (e) colorizing the target for display.

Fast target extraction from thermal imagery

A method of forming an output image based on first and second input images includes the steps of: (a) selecting a desired mix-ratio between the first and second input images; (b) determining an angle &#x3c6; based on the selected mix-ratio; and (c) extending a diagonal line, at the angle of &#x3c6; between a vertical axis and a horizontal axis, in which the vertical axis includes a first set of gray levels from the first input image and the horizontal axis includes a second set of gray levels from the second input image. The method further includes the steps of: (d) computing an area A included within the horizontal and vertical axes and the diagonal line, in order to determine a gray level value of a pixel of the output image based on a probability value of k=A/n, where, n is a maximum gray level value of each of the input images, and k varies from 0 to 1. In one embodiment, the fixed probability distribution is uniform, and the input and output image bit depths are equal to each other. Then the gray level value of z of the output image becomes A/n.

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Webster, NY, United States of America

Kenneth Michael Brodeur