EP0772158A2
Expired / Lapsed
EP
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Image processing system
Assignee: HP Inc
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Filing: 1996-10-14
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Granted: —
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Expires: 2016-10-14
Abstract
Abstract A method of operating a computer to produce contrast enhanced digital images produces a histogram (211) having a first axis corresponding to a measurable property (e.g., luminance) and a second axis corresponding to a count of particular value for the measurable property. This histogram is divided into clusters and histogram equalisation or stretching is performed on each cluster to modify the histogram. The modified histogram is used to adjust the value of the first measurable property to enhance an image contrast. The histogram is divided into clusters using a pattern matching technique, gaussian distributions and uniform distributions being separated into individual clusters.
Inventors
- 👤 Daniel R. Tretter
Bibliographic Details
Application Number
—
Jurisdiction
EP
Data Source
google_patents
Last Synchronized
2026-11-09 11:27
CPC Classifications
G; G06; G06T; G06T5/00; G06T5/90; G06T5/92; G06T5/40
Claims Analysis
Total Claims: 15
Claim 1
Independent Claim
120 words
A method of operating a computer to produce contrast enhanced images, wherein an image is composed of a plurality of pixels, comprising the steps of: inputting (109) in digital form an original image into a storage unit of said computer; producing (509) a histogram of said digital form having a first axis corresponding to a first measurable property and a second axis corresponding to a count of pixels having a particular value for said first measurable property; dividing (511) said histogram into clusters; performing (515) histogram equalisation on each cluster thereby producing a modified histogram; and using (517) said modified histogram to adjust the value of said first measurable property in said digital form, thereby producing said contrast enhanced image.
Claim 2
Dependent Claim
22 words
A method as in Claim 1, wherein said dividing step comprises the step of partitioning the histogram into clusters of equal size.
Claim 3
Dependent Claim
29 words
A method as in Claim 1, wherein said dividing step comprises the step of detecting patterns in the histogram and dividing the histogram into clusters based on said patterns.
Claim 4
Dependent Claim
34 words
A method as in Claim 3, wherein said pattern detection comprises the steps of detecting regions in said histogram that resemble Gaussian distributions and detecting other regions in said histogram that resemble uniform distributions.
Claim 5
Dependent Claim
32 words
A method as in Claim 1, 2, 3 or 4, wherein for an RGB image the method comprises the step of converting said RGB image into a format having a luminance component.
Claim 6
Independent Claim
128 words
A method as in any preceding Claim, wherein said first measurable property is a light intensity measure and wherein for each light intensity value said count of pixels is a count of pixels having that particular light intensity, and wherein said histogram has an extent equal to the highest and lowest light intensity values in said original image, each cluster representing a range in said histogram, the sum of the histogram values for the range corresponding to the number of pixels having a light intensity within the range of the cluster; the method comprising the step of remapping cluster boundaries proportionally to the cluster's range (Ro), said number of pixels within said range (Ni), the total number of pixels in the image (Nt), and said histogram extent (Eo).
Claim 7
Dependent Claim
48 words
A method as in Claim 6, wherein said remapping step comprises the step of selecting a desired range for the histogram (Ed) of said output image; and stretching the width of each cluster according to the relationship: wherein w is a weighting factor ranging from 0 to 1.0.
Claim 8
Independent Claim
55 words
A method as in any preceding Claim, wherein for an image with a digital form which comprises a second measurable property, said generating step comprises the step of for each pixel in said contrast enhanced image, limiting the value of said first measurable property as a function of the value of said second measurable property.
Claim 9
Dependent Claim
79 words
A method as in Claim 8, comprising the steps of generating a table of maximum values of said first measurable property as a function of said second measurable property; said limiting step comprising, for each value V of said second measurable property, the step of retrieving from said table the maximum value M for said first measurable property corresponding to said value V and if said value V exceeds said maximum value H setting the value V to H.
Claim 10
Dependent Claim
206 words
An image processing system with a memory for producing contrast enhanced images, comprising a histogram producing unit (209) operable to produce a histogram data structure in said memory, said histogram corresponding to an image composed of a plurality of pixels and including, for each level of a first property of said pixels, a count of pixels having a value for said first property corresponding to said level, thereby defining an extent for said histogram corresponding to a range represented by the lowest such level having a non-zero count and the highest such level having a non-zero count; a clusterizer (213) connected to said histogram data structure and operable to partition said histogram data structure into clusters; a histogram cluster boundary adjuster (219) connected to said histogram data structure and operable to adjust boundaries of each cluster in said data structure such that said boundaries conform to a function having the parameters cluster width (Ro), a count of pixels in the cluster (Ni), a count of pixels in the image (Nt), the original histogram extent (Eo), and a desired histogram extent (Ed); and a histogram adjuster connected to said histogram data structure and operable to modify the histogram for each such cluster according to a desired characteristic.
Claim 11
Dependent Claim
55 words
An image processing system as in Claim 11, wherein said histogram adjuster is (i) a histogram equaliser (219) and said desired characteristic is uniform distribution of pixels contained in said cluster, or (ii) a histogram stretcher and said desired characteristic is conformance of the histogram extend to said desired histogram extent (Ed) for each cluster.
Claim 12
Dependent Claim
32 words
An image processing system as in Claim 10 or 11, comprising an image translator (207) containing transformations between a first image format and a second image format that includes said first property.
Claim 13
Dependent Claim
42 words
An image processing system as in Claim 10, 11 or 12, comprising an image generator connected to said histogram data structure and said original image, and operable to generate a contrast enhanced image from said histogram data structure and said original image.
Claim 14
Dependent Claim
47 words
An image processing system as in any one of Claims 10 to 14, wherein said function is: R n =( w ( N i N t )+(1- w )( R o E o )) E d wherein w is a weighting factor ranging from 0 to 1.0.
Claim 15
Dependent Claim
42 words
An image processing system as in any one of Claims 10 to 14, wherein said clusterizer comprises a pattern recognizer operable to detect areas approximating uniform distribution and areas approximating Gaussian distribution, and to partition the histogram on boundaries between such areas.
References Cited (Backward Citations)
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