Patent US5880767A successfully refreshed from Google Patents.
US5880767A
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Perceptual image resolution enhancement system
Assignee: Hewlett Packard Development Co LP
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Filing: 1996-09-11
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Granted: 1999-03-09
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Expires: 2016-09-11
Abstract
Abstract The present invention provides an effective, low cost method and system for enhancing various types of images including photograph, CD, video, and graphic art images. The method of enhancing the input image, includes the steps of: filtering the input image to extract m different frequency components r k ; adaptively sharpening the m different frequency components r k , where the amount of sharpening for each component r k corresponds to a sharpening function g k r k !; and adding the adaptively sharpened m different frequency components g k r k ! to the input image. Because the sharpening function is typically nonlinear, the step of determining the value of the adaptive frequency component corresponding to the sharpening function is achieved by mapping the filtered component by the corresponding sharpening function.
Inventors
- 👤 Samson J. Liu
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-11-07 17:57
CPC Classifications
G; G06; G06T; G06T5/00; G06T5/73; G06T5/75; G06T5/20
Claims Analysis
Total Claims: 28
Claim 1
Independent Claim
91 words
A method of sharpening an input image, the method including the steps of: filtering the input image to extract m different frequency components r k ; adaptively sharpening the m different frequency components r k according to an adaptive sharpening function g k r k !, where an amount of sharpening for each component r k corresponds to a magnitude of the frequency component r k where m is a positive integer number; and adding the adaptively sharpened m different frequency components g k r k ! to the input image.
Claim 2
Independent Claim
91 words
A method of sharpening an input image, the method including the steps of: filtering the input image to extract m different frequency components r k ; adaptively sharpening the m different frequency components r k according to an adaptive sharpening function g k r k !, where an amount of sharpening for each component r k corresponds to a magnitude of the frequency component r k where m is a positive integer number; and adding the adaptively sharpened m different frequency components g k r k ! to the input image.
Claim 3
Dependent Claim
27 words
The method according to claim 1 wherein the sharpening function g k r k ! for adaptively sharpening the m different frequency components r k is nonlinear.
Claim 4
Dependent Claim
49 words
The method according to claim 1 wherein the sharpening function g k r k ! for adaptively sharpening the m different frequency components r k is equal to αf k r k ! where α k is a gain and f k r k ! is the sharpening function.
Claim 5
Dependent Claim
63 words
The method according to claim 1 wherein the step of adding the adaptively sharpened m different frequency components g k r k ! to the input image is an output image y, the output image y being mathematically expressed by ##EQU6## where x is the original image, h k is the bandpass filter, and g k r k ! is the sharpening function.
Claim 6
Dependent Claim
52 words
The method according to claim 1 wherein the step of adaptively sharpening the m different frequency components r k , where the amount of sharpening for each component r k corresponds to the sharpening function g k r k ! is achieved by mapping the filtered component by the corresponding sharpening function.
Claim 7
Dependent Claim
55 words
The method according to claim 1 wherein for the case where m=1 the step of filtering the input image to extract m different frequency components r k further includes the steps of: filtering the m different frequency components r k using a low pass filter and subtracting the result filtered image from the original image.
Claim 8
Dependent Claim
15 words
The method recited in claim 6 wherein the low pass filter is a linear filter.
Claim 9
Dependent Claim
17 words
The method recited in claim 6 wherein the low pass filter is an order statistics nonlinear filter.
Claim 10
Dependent Claim
43 words
The method recited in claim 3 wherein for the case where m=1 the function f k r k ! can be mathematically represented by ##EQU7## where a, b, and L are free parameters that control a relative amount of edge and texture sharpening.
Claim 11
Dependent Claim
22 words
The method recited in claim 1 further including the step of performing edge overshoot reduction on the edge pixels of the image.
Claim 12
Dependent Claim
96 words
The method recited in claim 10 wherein the step of performing edge overshoot reduction includes the steps of: determining whether a current pixel is an edge pixel; comparing the edge pixel to a minimum edge overshoot value; replacing the edge pixel value with the minimum edge overshoot value when the edge pixel value is less than the minimum edge overshoot value; comparing the edge pixel to a maximum edge overshoot value; and replacing the edge pixel value with the maximum edge overshoot value when the edge pixel value is greater than the minimum edge overshoot value.
Claim 13
Independent Claim
83 words
A method of sharpening an input image comprised of a plurality of pixels, the method including the steps of: filtering the input image to extract m different frequency components r k where m is a positive integer number r k ; sharpening the m different frequency components r k ; adding the sharpened m different frequency components to the input image; and performing edge overshoot reduction on a result of the addition of the sharpened m different frequency components and the input image.
Claim 14
Independent Claim
83 words
A method of sharpening an input image comprised of a plurality of pixels, the method including the steps of: filtering the input image to extract m different frequency components r k where m is a positive integer number r k ; sharpening the m different frequency components r k ; adding the sharpened m different frequency components to the input image; and performing edge overshoot reduction on a result of the addition of the sharpened m different frequency components and the input image.
Claim 15
Dependent Claim
96 words
The method recited in claim 12 wherein the step of performing edge overshoot reduction includes the steps of: determining whether a current pixel is an edge pixel; comparing the edge pixel to a minimum edge overshoot value; replacing the edge pixel value with the minimum edge overshoot value when the edge pixel value is less than the minimum edge overshoot value; comparing the edge pixel to a maximum edge overshoot value; and replacing the edge pixel value with the maximum edge overshoot value when the edge pixel value is greater than the minimum edge overshoot value.
Claim 16
Dependent Claim
98 words
An image resolution enhancement system, the image resolution enhancement system including: a filtering means for extracting m different frequency components r k from an input image where m is a positive integer number; a means for adaptively sharpening the m different frequency components r k according to an adaptive sharpening function g k r k !, where an amount of sharpening for each component r k corresponds to a magnitude of the frequency component r k ; and a means for adding the adaptively sharpened m different frequency components g k r k ! to the input image.
Claim 17
Dependent Claim
98 words
An image resolution enhancement system, the image resolution enhancement system including: a filtering means for extracting m different frequency components r k from an input image where m is a positive integer number; a means for adaptively sharpening the m different frequency components r k according to an adaptive sharpening function g k r k !, where an amount of sharpening for each component r k corresponds to a magnitude of the frequency component r k ; and a means for adding the adaptively sharpened m different frequency components g k r k ! to the input image.
Claim 18
Dependent Claim
22 words
The image resolution enhancement system according to claim 14 wherein the values of the sharpening function are stored in a look-up table.
Claim 19
Dependent Claim
104 words
An image resolution enhancement system, the image resolution enhancement system including: a filtering means for extracting m different frequency components r k from an input image wherein m is a positive integer number; a means for sharpening the m different frequency components r k where an amount of sharpening for each component r k corresponds to a magnitude of the frequency component r k ; a means for adding the sharpened m different frequency components to the input image; and a means for performing edge overshoot reduction on a result of the addition of the sharpened m different frequency components and the input image.
Claim 20
Dependent Claim
104 words
An image resolution enhancement system, the image resolution enhancement system including: a filtering means for extracting m different frequency components r k from an input image wherein m is a positive integer number; a means for sharpening the m different frequency components r k where an amount of sharpening for each component r k corresponds to a magnitude of the frequency component r k ; a means for adding the sharpened m different frequency components to the input image; and a means for performing edge overshoot reduction on a result of the addition of the sharpened m different frequency components and the input image.
Claim 21
Independent Claim
149 words
A method of sharpening an input image, the method including the steps of: filtering the input image to extract m different frequency components r k ; adaptively sharpening the m different frequency components r k accoding to an adaptive sharpening function g k r k !, where an amount of sharpening for each component r k corresponds to a magnitude of the frequency component r k adding the adaptively sharpened m different frequency components g k r k ! to the input image, wherein the step of adding the adaptively sharpened m different frequency components g k r k ! to the input image is an output image y, the output image y being mathematically expressed by ##EQU8## where x is the original image, h k is a bandpass filter, and g k r k ! is the sharpening function, wherein m is greater than or equal to 2.
Claim 22
Independent Claim
149 words
A method of sharpening an input image, the method including the steps of: filtering the input image to extract m different frequency components r k ; adaptively sharpening the m different frequency components r k accoding to an adaptive sharpening function g k r k !, where an amount of sharpening for each component r k corresponds to a magnitude of the frequency component r k adding the adaptively sharpened m different frequency components g k r k ! to the input image, wherein the step of adding the adaptively sharpened m different frequency components g k r k ! to the input image is an output image y, the output image y being mathematically expressed by ##EQU8## where x is the original image, h k is a bandpass filter, and g k r k ! is the sharpening function, wherein m is greater than or equal to 2.
Claim 23
Independent Claim
95 words
A method of sharpening an input image, the method including the steps of: filtering the input image to extract m different frequency components r k ; adaptively sharpening the m different frequency components r k according to an adaptive sharpening function g k r k !, where an amount of sharpening for each component r k corresponds to a magnitude of the frequency component r k , and where m is greater than or equal to two; and adding the adaptively sharpened m different frequency components g k r k ! to the input image.
Claim 24
Independent Claim
95 words
A method of sharpening an input image, the method including the steps of: filtering the input image to extract m different frequency components r k ; adaptively sharpening the m different frequency components r k according to an adaptive sharpening function g k r k !, where an amount of sharpening for each component r k corresponds to a magnitude of the frequency component r k , and where m is greater than or equal to two; and adding the adaptively sharpened m different frequency components g k r k ! to the input image.
Claim 25
Dependent Claim
27 words
The method according to claim 18 wherein the sharpening function g k r k ! for adaptively sharpening the m different frequency components r k is nonlinear.
Claim 26
Dependent Claim
39 words
The method according to claim 18 wherein the sharpening function g k r k ! for adaptively sharpening the m different frequency components r k is equal to αf k r k ! where α k is a gain.
Claim 27
Independent Claim
91 words
A method of sharpening an input image, the method including the steps of: filtering the input image to extract m different frequency components r k ; adaptively sharpening every filtered coefficient in each of the m different frequency components r k according to an adaptive sharpening function g k r k !, where an amount of sharpening for each component r k corresponds to a magnitude of the frequency component r k ; and adding the adaptively sharpened m different frequency components g k r k ! to the input image.
Claim 28
Independent Claim
91 words
A method of sharpening an input image, the method including the steps of: filtering the input image to extract m different frequency components r k ; adaptively sharpening every filtered coefficient in each of the m different frequency components r k according to an adaptive sharpening function g k r k !, where an amount of sharpening for each component r k corresponds to a magnitude of the frequency component r k ; and adding the adaptively sharpened m different frequency components g k r k ! to the input image.
References Cited (Backward Citations)
USPTO Annuity & Maintenance Windows
| Annuity Stage | Window Opens | Payment Deadline | Surcharge Period Until | Estimated Fee | Status |
|---|---|---|---|---|---|
| 3.5 Years (Year 4) | 2002-03-08 | 2002-09-07 | 2003-03-09 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 2006-03-08 | 2006-09-07 | 2007-03-09 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2010-03-08 | 2010-09-07 | 2011-03-09 | $7700.00 | Window Closed / Lapsed |