Eastman-Kodak Company

Navid Serrano

Edward B Gindele

Jeffrey Clarence Snyder

Edward Brooks Gindele

A method of estimating the noise in a digital image for use in subsequent image processing, includes receiving a source digital image having a plurality of pixels; selecting a pixel of interest; providing a plurality of orientations for the pixel of interest; using gradient analysis on the source digital image and the plurality of orientations to select the most suitable orientation for estimating noise for the pixel of interest; using the selected orientation in the pixel of interest to determine a noise-free pixel estimate for the pixel of interest; and repeating for other pixels of interest and using the noise-free pixel estimates to calculate a noise characteristic value representing the noise estimate for the source digital image.

Calculating noise estimates of a digital image using gradient analysis

A method of estimating noise in a digital image receiving a digital image; providing a first statistical table related to noise provided by an image source; and using the pixels of the digital image to calculate a second statistical table related to the noise provided by the image source in capturing the image. The method further includes using the first statistical table and the second statistical table to provide an updated third statistical table related to the noise provided by the image source in capturing the image; and calculating a noise characteristic table from the third statistical table for use in enhancing the digital image.

Estimating noise for a digital image utilizing updated statistics

A method for estimating a noise characteristic value for a plurality of digital images that are affected by a common noise source includes receiving a plurality of source digital images that are affected by a common noise source, each source digital image including a plurality of pixels; calculating a total number of pixels included in the source digital images; and receiving a predetermined target number of noise estimates to be calculated for the source digital images. The method also includes using the total number of pixels and the predetermined target number of noise estimates to calculate one or more pixel sampling parameters for the source digital images; using the source digital images and the one or more pixel sampling parameters to calculate a predetermined number of noise estimates; and using the noise estimates to calculate a noise characteristic value for the source digital images.

Calculating noise from multiple digital images having a common noise source

A method of spatially filtering a digital image includes receiving a source digital image including pixels corresponding to one or more different colors; selecting a pixel of interest in the source digital image; calculating two or more noise free pixel estimates for the pixel of interest using pixel values sampled in a local region about the pixel of interest; selecting a final noise free pixel estimate for the pixel of interest from the noise free pixel estimates; and repeating for other pixels in the source digital image to provide a spatially filtered digital image.

Method of spatially filtering digital image for noise removal, noise estimation or digital image enhancement

A method of calculating a noise characteristic value for a source digital image includes receiving a source digital image including pixels corresponding to two or more different colors; using pixel values corresponding to a first color to produce at least one color correlation term for pixels corresponding to a second color which respectively indicate the extent of the noise content in the pixel values of the second color; and using the color correlation term to calculate a noise characteristic value for the pixels corresponding to the second color.

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Rochester, NY, United States of America

Navid Serrano