Honeywell International Inc.

Venkatagiri Subbaraya Rao

Jeremy Craig Wilson

Kamini Kanta Mohanty

Vijendran Gopalan Venkoparao

Rudra N Hota

Mahesh K Gelinboina

A system and method for filtering video noise is provided. Video generated under low lighting conditions is susceptible to increased noise and graininess, which increases the required storage space required for recording the noisy video. The provided system and method for filtering video noise reduces noise in low-light video by estimating the noise profile associated with at least one video frame; discriminating between chrominance noise and luminance noise in said noise profile; applying predetermined filter criteria to said chrominance noise to estimate the parameters for luminance noise filtering; applying said luminance noise filtering parameters to filter the luminance noise; and generating a first filtered output of a frame by logical combination of outputs obtained from luminance noise filter and chrominance noise filter.

Method for digital noise reduction in low light video

Real-time image stabilization using computationally efficient corner detection and correspondence is provided. The real-time image stabilization performs a scene learning process on a first frame of an input video to obtain reference features and a detection threshold value. The presence of jitter is determined in a current frame of the input video by comparing features of the current frame against the reference features using the detection threshold value. If the current frame is found to be unstable, corner points are obtained from the current frame. The obtained corner points are matched against reference corner points of the reference features. If the number of matched corner points is not less than a match point threshold value, the current frame is modeled using random sample consensus. The current frame is corrected to compensate for the jitter based on the results of the modeling.

Video stabilization in real-time using computationally efficient corner detection and correspondence

A computer assisted method identifies characteristics of a flare. A digital image of the flare is obtained, such as by a color digital video camera and a region of interest likely containing the flare is identified. Flare pixels within the region of interest are identified and color information is extracted from such flare pixels. The extracted color information is associated to characterizations of the flare, and an operator is provided an alert when such characterizations indicate an abnormal flare.

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Bengaluru, India

Venkatagiri Subbaraya Rao