Method for random point and patterned noise reduction in digital images
First Claim
Patent Images
1. A method for processing image data comprising:
- processing input image data by identifying features of interest to produce processed image data;
characterizing spike noise in the input image data; and
performing spike noise dependent blending of data derived from the input image data with the processed image data based upon the characterization.
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Accused Products
Abstract
A technique is provided for filtering noise in digital image data, particularly random point or spike noise. Image data may be rank order filtered and absolute differences between ordered values computed to create a mask. Blending is performed based upon a likelihood that individual pixels are or exhibit spike noise. The rank order filtered values may be used directly for blending, or the original image may be shrunk and then expanded to provide a rapid and computationally efficient spike noise reduction alternative.
23 Citations
26 Claims
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1. A method for processing image data comprising:
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processing input image data by identifying features of interest to produce processed image data; characterizing spike noise in the input image data; and performing spike noise dependent blending of data derived from the input image data with the processed image data based upon the characterization. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A method for processing image data comprising:
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processing input image data by identifying features of interest to produce processed image data; characterizing spike noise in the input image data by rank-order filtering the input image data, computing an absolute difference between the rank-order filtered input image data and the input image data, and generating a multi-level mask of spike noise likelihood based upon the absolute differences; and performing spike noise dependent blending of input image data with the processed image data based upon the multi-level mask. - View Dependent Claims (9, 10)
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11. A method for processing image data comprising:
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processing input image data by identifying features of interest to produce processed image data; determining a likelihood that discrete picture elements in the input image data exhibit spike noise; and blending data derived from the input image data with the processed image data via weighting factors determined based upon the likelihood that the discrete picture elements exhibit spike noise. - View Dependent Claims (12, 13, 14, 15, 16, 17)
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18. A system for processing image data comprising:
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a memory circuit for storing input image data; a processing module for processing the input image data to generate processed image data; and a spike noise blending module configured to determine a likelihood that discrete picture elements in the input image data exhibit spike noise, and to blend data derived from the input image data with the processed image data via weighting factors determined based upon the likelihood that the discrete picture elements exhibit spike noise. - View Dependent Claims (19, 20)
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21. A system for processing image data comprising:
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means for processing input image data by identifying features of interest to produce processed image data; means for characterizing spike noise in the input image data; and means for performing spike noise dependent blending of data derived from the input image data with the processed image data based upon the characterization.
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22. A system for processing image data comprising:
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means for processing input image data by identifying features of interest to produce processed image data; means for characterizing spike noise in the input image data by rank-order filtering the input image data, computing an absolute difference between the rank-order filtered input image data and the input image data, and generating a multi-level mask of spike noise likelihood based upon the absolute differences; and means for performing spike noise dependent blending of input image data with the processed image data based upon the multi-level mask.
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23. A system for processing image data comprising:
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means for processing input image data by identifying features of interest to produce processed image data; means for determining a likelihood that discrete picture elements in the input image data exhibit spike noise; and means for blending data derived from the input image data with the processed image data via weighting factors determined based upon the likelihood that the discrete picture elements exhibit spike noise.
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24. One or more computer readable mediums encoded with a computer program comprising:
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a routine for processing input image data by identifying features of interest to produce processed image data; a routine for characterizing spike noise in the input image data; and a routine for performing spike noise dependent blending of data derived from the input image data with the processed image data based upon the characterization.
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25. One or more computer readable mediums encoded with a computer program comprising:
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a routine for processing input image data by identifying features of interest to produce processed image data; a routine for characterizing spike noise in the input image data by rank-order filtering the input image data; a routine for computing an absolute difference between the rank-order filtered input image data and the input image data; a routine for generating a multi-level mask of spike noise likelihood based upon the absolute differences; and a routine for performing spike noise dependent blending of input image data with the processed image data based upon the multi-level mask.
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26. One or more computer readable mediums encoded with a computer program for processing image data, the computer program comprising:
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a routine for processing input image data by identifying features of interest to produce processed image data; a routine for determining a likelihood that discrete picture elements in the input image data exhibit spike noise; and a routine for blending data derived from the input image data with the processed image data via weighting factors determined based upon the likelihood that the discrete picture elements exhibit spike noise.
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Specification