Eastman-Kodak Company

Greg L Archer

Eric J Meisenzahl

Shen Wang

Larry W Wilkinson

David N Nichols

Dennis J Vankerkhove

A method for detecting and removing noise from an image, the method includes the steps of applying a frequency transform to the image for obtaining a magnitude image; comparing a threshold value to values of the magnitude image for obtaining thresholded values; setting one or more thresholded values to a predetermined value; and reconstructing the image from the magnitude image having the predetermined values for removing noise from the image.

Use of frequency transform in the analysis of image sensors

A method for detecting and removing noise from an image, the method includes the steps of applying a frequency transform to the image for obtaining a magnitude image; applying a threshold value to values of the magnitude image for obtaining threshold values; setting one or more threshold values to a predetermined value; and reconstructing the image from the magnitude image having the predetermined values for removing noise from the image.

Use of frequency transforms in the analysis of image sensors

The present invention uses five regions of interest, 4 corners and 1 center to do Fourier Transform analysis to mark rough location of the streaks, if there is any. It sets the small window around the center in each Fourier Transform ROI to zero to mask the cluster of bright points caused by the lens rolloff or other noises. It use iterative linear regression to remove the random outliers and to search the best possible linear pattern. If it finds any streaks, it calculates the angle and converts it to the streak angle in spatial domain. Once a streak is detected, it can be removed by applying an inverse Fourier Transform on the processed magnitude and original phase Fourier Transform images.

Method for detecting streaks in digital images

A method for testing an image sensor for photoresponse uniformity, the method includes the steps of providing a light source having inherent non-uniform light intensity characteristics; providing a light sensing device for measuring an intensity response of the light source on a predetermined image plane; determining an area on the image plane corresponding to an area for the image sensor; measuring pre-selected points of the determined area by the light sensing device for measuring incident light intensity from the light source on the image plane; interpolating non-measured points on the image plane representing an estimate of the non-uniformity of the light source at the non-measured points; inverting the interpolated image to represent the inverse of the light source non-uniformity; and applying the inverted image to the response of the image sensor which compensates for light source non-uniformity and enables the ability to quantify accurately the non-uniformity of the image sensor.

Method of testing the uniformity of an image sensor

A two dimensional moving averaging filter is provided using a computational element coupled to a memory means which contains an electronic version of a two dimensional array of pixel values with N rows and M columns and a temporary memory buffer having a dimension of M columns by R&plus;1 rows that is operatively coupled to receive data from the array. Each of the M columns within the temporary memory buffer is summed and the summated column values are placed into the &ldquo;R&plus;1&rdquo; row of the temporary memory wherein a neighborhood filter is formed by secondly summing a predetermined number, &ldquo;C&rdquo;, of the summated column values such that the neighborhood filter contains a summation for a neighborhood the pixel array values of &ldquo;R&rdquo; rows by &ldquo;C&rdquo; columns. The summated neighborhood is averaged by dividing by the number of elements within the neighborhood (R&times;C) to gain an averaged center to the neighborhood filter and this averaged center is placed into its representative position of the pixel value that is currently being filtered within the two dimensional array. The neighborhood filter is then moved to the next pixel position to be filtered by adding a new summated column value from the &ldquo;R&plus;&rdquo; row of the temporary memory buffer to the neighborhood filter and subtracting an oldest summated column value within the R&plus;1 row from the neighborhood filter. After processing an entire row, the oldest row is subtracted from the extra row summation and the next sequential row is added to the extra row.

Two dimensional moving average filter

A rank filter suitable for use in real-time signal processing and image processing applications, for example, for improving an image. The rank filter can be implemented in software or hardware, employed in single- and multi-dimensions, and within any specified window. A link-list algorithm is combined with a memory array for storing and ordering the data.

Growing community of inventors

Rochester, NY, United States of America

Greg L Archer