EP0780791A2
Expired / Lapsed
EP
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Automatic tone scale adjustment using image activity measures
Assignee: Eastman Kodak Co
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Filing: 1996-12-05
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Granted: —
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Expires: 2016-12-05
Abstract
Abstract A method of automatic tone scale adjustment for digital radiographic images comprising the steps of:providing an input digital radiographic image;estimating the image noise as a function of code value of the image;determining the range of code values in the input image;determining which way the input image should be processed;determining a bounding box which contains the region of interest of the input image;computing the image activity histogram of the input image;determining four points from the image activity histogram;constructing the tone-scale curve for the input image; andmapping the input image through the tone-scale curve to produce an output image with good tone scale.
Inventors
- 👤 Hsien-Che Lee
- 👤 Lori Lynn Barski
- 👤 Robert Allen Senn
Bibliographic Details
Application Number
—
Jurisdiction
EP
Data Source
google_patents
Last Synchronized
2026-11-07 13:00
CPC Classifications
G; G06; G06T; G06T5/00; G06T5/90; G06T5/92; G06T5/40; G06T2207/00; G06T2207/10; G06T2207/10116
Claims Analysis
Total Claims: 10
Claim 1
Independent Claim
110 words
A method of automatic tone scale adjustment for digital radiographic images comprising the steps of: providing an input digital radiographic image; estimating the image noise as a function of code value of said image; determining the range of code values in said input image; determining which way said input image should be processed; determining a bounding box which contains the region of interest of said input image; computing the image activity histogram of said input image; determining four points from said image activity histogram; constructing the tone-scale curve for said input image; and mapping said input image through said tone-scale curve to produce an output image with good tone scale.
Claim 2
Dependent Claim
25 words
The method of claim 1 wherein said providing step includes converting an x-ray image stored in a storage phosphor into said input digital radiographic image.
Claim 3
Dependent Claim
24 words
The method of claim 1 wherein said providing step includes digitizing a radiographic image on x-ray film to produce said input digital radiographic image.
Claim 4
Dependent Claim
46 words
The method of claim 1 wherein said estimating step includes the steps of exposing a gray scale of uniform patches at different exposures, calculating noise from the standard deviation of the code values in each uniformly exposed area, and interpolating the noise measurements of neighboring exposures.
Claim 5
Dependent Claim
65 words
The method of claim 1 wherein said estimating step includes the steps of computing the edge gradient of every pixel of the input image to distinguish the uniform area from the busy area in said image, estimating the noise value from the standard deviation in the uniform area, and interpolating the noise at any level of code value from the noise measurement of neighboring exposures.
Claim 6
Dependent Claim
109 words
The method of claim 1 wherein said step of determining the range of code values in said input image includes the steps of: calculating the code-value histogram, setting mincode = the smallest code value in the histogram that has more than 10 pixels, setting maxcode = the largest code value in the histogram that has more than 10 pixels, finding the background peak within an adaptive interval below maxcode, if the background peak is found, determining the first valley to the left of the peak as the right-bound, if the peak is not found, then setting right-bound = maxcode - 2* NOISE, setting the left-bound = mincode + 2*NOISE.
Claim 7
Dependent Claim
89 words
The method of claim 1 wherein said step of determining which way said input image should be processed includes the steps of: extracting the most modulated segments from all image lines in the horizontal direction and calculate the average length, extract the most modulated segments from all image lines in the vertical direction and calculate the average length, and if the average length of the horizontal segments is shorter than that of the vertical segments, then the image activity will be calculated with the horizontal segments, or else, vertical.
Claim 8
Independent Claim
97 words
A method of extracting important body part information from a digital radiographic image, comprising the steps of: (a) processing the digital image on a line by line basis; (b) partitioning each image line into separate segments, delimited by transition intervals that correspond to the transitions between foreground, and background, background and body part, and foreground and body part; (c) fitting a linear function to each line segment to determine if important signal modulation exists in that segment; and (d) selecting the most modulated segment from each image line to estimate the region of interest in the image.
Claim 9
Independent Claim
130 words
A method of extracting the important range of code values from an input digital image by computing image activity as a function of code value, comprising the steps of: (a) processing the digital image on a line by line basis; (b) calculating image activity at each pixel for each image line; (c) accumulating the image activity for each code value from each image line to form a cumulative activity histogram as a function of code value; and (d) locating the highest peak(s) of the activity histogram and one point on each side (the left and the right) of the peak(s) wherein the histogram height falls below certain thresholds; and (e) extracting the range of code values between the left point and the right point, as identified in the previous step.
Claim 10
Independent Claim
143 words
A method of extracting the important range of code values from an input digital image by counting the number of level-crossings for each code value, comprising the steps of: (a) processing the digital image on a line by line basis; (b) for each image line, updating an array that keeps track of the number of sign changes for each code value; (c) accumulating the number of sign changes for each code value from each image line to form a cumulative histogram of level-crossings as a function of code value; and (d) locating the highest peak of the level-crossing histogram and one point on each side (the left and the right) of the peak where the histogram height falls below certain criteria; and (e) extracting the range of code values between the left point and the right point, as identified in the previous step.
References Cited (Backward Citations)
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