Methods and systems for suppressing noise in images
First Claim
Patent Images
1. A method comprising:
- receiving a plurality of video image frames;
constructing a plurality of spatiotemporal volumes by stacking together a plurality of image blocks extracted from same or different spatial positions on different video image frames along a trajectory of estimated motion from the video image frames;
filtering the spatiotemporal volumes, wherein the filtering models both a random noise (RND) component and a fixed pattern noise (FPN) component in the video image frames to suppress both types of noise, and wherein the filtering is adaptively performed based at least on the estimated motion captured in each spatiotemporal volume to suppress the FPN component; and
aggregating the image blocks from the filtered spatiotemporal volumes to generate a plurality of filtered video image frames.
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Abstract
Various techniques are disclosed to effectively suppress noise in images (e.g., video or still images). For example, noise in images may be more accurately modeled as having a structured random noise component and a structured fixed pattern noise (FPN) component. Various parameters of noise may be estimated robustly and efficiently in real time and in offline processing. Noise in images may be filtered adaptively, based on various noise parameters and motion parameters. Such filtering techniques may effectively suppress noise even in images that have a prominent FPN component, and may also improve effectiveness of other operations that may be affected by noise.
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Citations
25 Claims
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1. A method comprising:
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receiving a plurality of video image frames; constructing a plurality of spatiotemporal volumes by stacking together a plurality of image blocks extracted from same or different spatial positions on different video image frames along a trajectory of estimated motion from the video image frames; filtering the spatiotemporal volumes, wherein the filtering models both a random noise (RND) component and a fixed pattern noise (FPN) component in the video image frames to suppress both types of noise, and wherein the filtering is adaptively performed based at least on the estimated motion captured in each spatiotemporal volume to suppress the FPN component; and aggregating the image blocks from the filtered spatiotemporal volumes to generate a plurality of filtered video image frames. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12)
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13. A system comprising:
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a video interface configured to receive a plurality of video image frames; a processor in communication with the video interface and configured to; construct a plurality of spatiotemporal volumes by stacking together a plurality of image blocks extracted from same or different spatial positions on different video image frames along a trajectory of estimated motion from the video image frames, filter the spatiotemporal volumes, wherein the filtering models both a random noise (RND) component and a fixed pattern noise (FPN) component in the video image frames to suppress both types of noise, and wherein the filtering is adaptively performed based at least on the estimated motion captured in each spatiotemporal volume to suppress the FPN component, and aggregate the image blocks from the filtered spatiotemporal volumes to generate a plurality of filtered video image frames; and a memory in communication with the processor and configured to store the video image frames. - View Dependent Claims (14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25)
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Specification