US 7,639,849 B2
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`29
`It may be desirable to use different specific noise reduction
`methodsfor different images or image types (such as amam-
`mogram; a chest image; a CT, MRI, or PET scan). Profiles
`may be created, for example, that link the use of a specific
`program to the use of a specific noise reduction method, or
`hatlink specific images to the use of specific noise reduction
`methods. Such a profile may be created at least in part in
`software. Detecting which noise reduction method to apply
`may be done automatically according to the image or video
`sequence to be shownonthe display (for instance, based on
`without limitation) neural networks that classify images or
`on statistical characteristics of the images/video). Alterna-
`ively or additionally, such detection may be based on inputs
`hints or messages) from the applications running on the host
`PC or oninputs of the user of the display. Embodiments may
`also be configured suchthatdifferentparts ofthe display may
`simultaneously use different noise reduction methods, as in a
`
`case where onthe left-hand side a PET image is shown andon
`the right-hand side a CT image is shown, for example. In
`some cases, it may be desirable to change the type of noise
`reduction algorithm used dynamically over time.
`Combinations of techniques as described above (such as
`visibility analysis, tailoring correction according to diagnos-
`tic relevance, frequency-based correction) are also expressly
`contemplated, as are applications of such combinations to
`greyscale images and to color images as appropriate.
`FIG. 21 showsa flowchart of a method M100 according to
`an embodiment. For each ofa plurality of pixels of a display,
`task T100 obtains a measureofa light-output responseofat
`least a portion of the pixel at each of a plurality of driving
`levels. For example, task T100 may obtain the measures from
`an image capturing device or mayretrieve the measures from
`storage (e.g. a non-volatile memory of the display). To
`increase a visibility of a characteristic of a displayed image
`during a use of the display, task T200 modifies a map that is
`based onthe obtained measures. Based on the modified map
`and an image signal, task 1300 obtains a display signal.
`Method M100 may be implemented as one or moresets(e.g.
`sequences) of instructions to be executed by one or more
`arrays of logic elements such as microprocessors, embedded
`controllers, or IP cores.
`FIG. 22 showsa flow chart of an implementation M110 of
`method M100. Task T150 creates a light-output map based on
`the obtained measures. For example, task 1150 may create a
`luminance map and/or a chrominance map. Task T210 is an
`implementation of task T200 that modifies the light-output
`map according to an image characteristic (e.g. a frequency or
`feature of interest). Task T250 calculates a correction map
`based on the modified light-output map. Task T310 is an
`implementation of task T300 that obtains a display signal
`based on the correction map and an image signal.
`FIG. 23 showsa flow chart of an implementation M120 of
`method M100. Task T260 calculates a correction map based
`on the light-output map. Task T220 is an implementation of
`task T200 that modifies the correction map according to an
`image characteristic (e.g. a frequencyor feature of interest).
`Task T320 is an implementation of task T300 that obtains a
`display signal based on the modified correction map and an
`image signal. In some applications, task T220 maybealtered
`at run-time to modify the correction map according to a
`different image characteristic.
`T'IG. 24 showsa block diagram ofan apparatus 100 accord-
`ing to an embodiment. Transformation circuit 110 stores a
`correction map that may include one or more lookuptables or
`other correction functions (e.g. accordingto a classification).
`For each pixel value, correction circuit 120 obtains a corre-
`sponding function or value from transformation circuit 110
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`and outputs a corrected value for display. As shown in ['IG.
`11, an apparatus according to an embodiment may also be
`configured to output display values directly from a lookup
`table. FIG. 25 showsa block diagram ofa system 200 accord-
`ing to an embodimentthat also includes video memory 40 and
`a display 130. Transformation circuit 110 may be imple-
`mented as an array of storage elements (e.g. a semiconductor
`memory such as DRAMorflash RAM) and may be imple-
`mented in the same storage device as video memory 40.
`FIG. 26 shows a block diagram of an implementation 102
`of apparatus 100 that includes a moditying circuit 130 con-
`figured to calculate the correction map of transformation
`circuit 110 (e.g. from another correction map, or from a
`light-output response map) according to a characteristic of an
`image feature that it is desired to distinguish. Modifying
`circuit 130 maybe implemented to perform any of the meth-
`odsor algorithmsdescribed herein,such as applying different
`gain factors to different frequency bands ofthe map. Oneor
`both of correction circuit 120 and modifying circuit 130 may
`be implementedas anarray of logic elements (e.g. a micro-
`processor or embedded controller) or as one of several tasks
`executing on suchanarray.
`The foregoing presentation of the described embodiments
`is provided to enable any personskilled in the art to make or
`use the present invention. Various modifications to these
`embodiments are possible, and the generic principles pre-
`sented herein may be applied to other embodiments as well.
`For example, operations described as obtaining or being per-
`formed on or with a luminance map mayalso be used to
`obtain or be performed on or with a chrominance map. An
`embodiment may be implemented in part or in whole as a
`hard-wired circuit; as a circuit configuration fabricated into a
`device such as an application-specific integrated circuit
`(ASIC), application-specific standard product (ASSP), or
`field-programmable gate array (FPGA) or other program-
`mable array.
`An embodiment may also be implemented in part or in
`whole as a firmware program loaded into non-volatile storage
`(for cxample, an array of storage clements such as flash RAM
`or ferroelectric memory) or a software program loaded from
`or into a data storage medium (for example, an array of
`storage elements such as a semiconductor or ferroelectric
`memory, or a magnetic or optical medium suchas a disk) as
`machine-readable code, such code being instructions execut-
`able byan array of lagic elements such as a microprocessor,
`embedded microcontroller, or other digital signal processing
`unt. Embodiments also include computer program products
`for executing any of the methods disclosed herein, and trans-
`mission of such a product over a communications network
`(e.g. a local area network, a wide area network,or the Inter-
`net). Thus, the present invention is not intendedto be limited
`to the embodiments shown abovebut rather is to be accorded
`the widest scope consistent with the principles and novel
`features disclosed in any fashion herein.
`Whatis claimedis:
`1.A method ofimageprocessing, said method comprising:
`for each of a plurality of pixels of a display, obtaining, a
`measure of alight-output response ofatleast a portion of
`the pixel at each of a plurality of driving levels:
`to increase a visibility of a characteristic of a displayed
`image during a use ofthe display, modifying a map that
`is based on the obtained measures; and
`based on the modified map and an imagesignal that rep-
`resents at least one physical and tangible object, obtain-
`ing a displaysignal that is configured to cause the dis-
`play to depict the at least one physical and tangible
`object.
`
`
`
`
`
`29
`It may be desirable to use different specific noise reduction
`methodsfor different images or image types (such as amam-
`mogram; a chest image; a CT, MRI, or PET scan). Profiles
`may be created, for example, that link the use of a specific
`program to the use of a specific noise reduction method, or
`hatlink specific images to the use of specific noise reduction
`methods. Such a profile may be created at least in part in
`software. Detecting which noise reduction method to apply
`may be done automatically according to the image or video
`sequence to be shownonthe display (for instance, based on
`without limitation) neural networks that classify images or
`on statistical characteristics of the images/video). Alterna-
`ively or additionally, such detection may be based on inputs
`hints or messages) from the applications running on the host
`PC or oninputs of the user of the display. Embodiments may
`also be configured suchthatdifferentparts ofthe display may
`simultaneously use different noise reduction methods, as in a
`
`case where onthe left-hand side a PET image is shown andon
`the right-hand side a CT image is shown, for example. In
`some cases, it may be desirable to change the type of noise
`reduction algorithm used dynamically over time.
`Combinations of techniques as described above (such as
`visibility analysis, tailoring correction according to diagnos-
`tic relevance, frequency-based correction) are also expressly
`contemplated, as are applications of such combinations to
`greyscale images and to color images as appropriate.
`FIG. 21 showsa flowchart of a method M100 according to
`an embodiment. For each ofa plurality of pixels of a display,
`task T100 obtains a measureofa light-output responseofat
`least a portion of the pixel at each of a plurality of driving
`levels. For example, task T100 may obtain the measures from
`an image capturing device or mayretrieve the measures from
`storage (e.g. a non-volatile memory of the display). To
`increase a visibility of a characteristic of a displayed image
`during a use of the display, task T200 modifies a map that is
`based onthe obtained measures. Based on the modified map
`and an image signal, task 1300 obtains a display signal.
`Method M100 may be implemented as one or moresets(e.g.
`sequences) of instructions to be executed by one or more
`arrays of logic elements such as microprocessors, embedded
`controllers, or IP cores.
`FIG. 22 showsa flow chart of an implementation M110 of
`method M100. Task T150 creates a light-output map based on
`the obtained measures. For example, task 1150 may create a
`luminance map and/or a chrominance map. Task T210 is an
`implementation of task T200 that modifies the light-output
`map according to an image characteristic (e.g. a frequency or
`feature of interest). Task T250 calculates a correction map
`based on the modified light-output map. Task T310 is an
`implementation of task T300 that obtains a display signal
`based on the correction map and an image signal.
`FIG. 23 showsa flow chart of an implementation M120 of
`method M100. Task T260 calculates a correction map based
`on the light-output map. Task T220 is an implementation of
`task T200 that modifies the correction map according to an
`image characteristic (e.g. a frequencyor feature of interest).
`Task T320 is an implementation of task T300 that obtains a
`display signal based on the modified correction map and an
`image signal. In some applications, task T220 maybealtered
`at run-time to modify the correction map according to a
`different image characteristic.
`T'IG. 24 showsa block diagram ofan apparatus 100 accord-
`ing to an embodiment. Transformation circuit 110 stores a
`correction map that may include one or more lookuptables or
`other correction functions (e.g. accordingto a classification).
`For each pixel value, correction circuit 120 obtains a corre-
`sponding function or value from transformation circuit 110
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`and outputs a corrected value for display. As shown in ['IG.
`11, an apparatus according to an embodiment may also be
`configured to output display values directly from a lookup
`table. FIG. 25 showsa block diagram ofa system 200 accord-
`ing to an embodimentthat also includes video memory 40 and
`a display 130. Transformation circuit 110 may be imple-
`mented as an array of storage elements (e.g. a semiconductor
`memory such as DRAMorflash RAM) and may be imple-
`mented in the same storage device as video memory 40.
`FIG. 26 shows a block diagram of an implementation 102
`of apparatus 100 that includes a moditying circuit 130 con-
`figured to calculate the correction map of transformation
`circuit 110 (e.g. from another correction map, or from a
`light-output response map) according to a characteristic of an
`image feature that it is desired to distinguish. Modifying
`circuit 130 maybe implemented to perform any of the meth-
`odsor algorithmsdescribed herein,such as applying different
`gain factors to different frequency bands ofthe map. Oneor
`both of correction circuit 120 and modifying circuit 130 may
`be implementedas anarray of logic elements (e.g. a micro-
`processor or embedded controller) or as one of several tasks
`executing on suchanarray.
`The foregoing presentation of the described embodiments
`is provided to enable any personskilled in the art to make or
`use the present invention. Various modifications to these
`embodiments are possible, and the generic principles pre-
`sented herein may be applied to other embodiments as well.
`For example, operations described as obtaining or being per-
`formed on or with a luminance map mayalso be used to
`obtain or be performed on or with a chrominance map. An
`embodiment may be implemented in part or in whole as a
`hard-wired circuit; as a circuit configuration fabricated into a
`device such as an application-specific integrated circuit
`(ASIC), application-specific standard product (ASSP), or
`field-programmable gate array (FPGA) or other program-
`mable array.
`An embodiment may also be implemented in part or in
`whole as a firmware program loaded into non-volatile storage
`(for cxample, an array of storage clements such as flash RAM
`or ferroelectric memory) or a software program loaded from
`or into a data storage medium (for example, an array of
`storage elements such as a semiconductor or ferroelectric
`memory, or a magnetic or optical medium suchas a disk) as
`machine-readable code, such code being instructions execut-
`able byan array of lagic elements such as a microprocessor,
`embedded microcontroller, or other digital signal processing
`unt. Embodiments also include computer program products
`for executing any of the methods disclosed herein, and trans-
`mission of such a product over a communications network
`(e.g. a local area network, a wide area network,or the Inter-
`net). Thus, the present invention is not intendedto be limited
`to the embodiments shown abovebut rather is to be accorded
`the widest scope consistent with the principles and novel
`features disclosed in any fashion herein.
`Whatis claimedis:
`1.A method ofimageprocessing, said method comprising:
`for each of a plurality of pixels of a display, obtaining, a
`measure of alight-output response ofatleast a portion of
`the pixel at each of a plurality of driving levels:
`to increase a visibility of a characteristic of a displayed
`image during a use ofthe display, modifying a map that
`is based on the obtained measures; and
`based on the modified map and an imagesignal that rep-
`resents at least one physical and tangible object, obtain-
`ing a displaysignal that is configured to cause the dis-
`play to depict the at least one physical and tangible
`object.
`
`
`
`US 7,639,849 B2
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`31
`2. The method of image processing according to claim 1,
`wherein the map comprisesat least one ofa luminance map of
`the display and a chrominance map ofthe display.
`3. The method of image processing according to claim 1,
`wherein said modifying a map is based on a characteristic of
`a feature to be detected during display of an image.
`4. The method of image processing according to claim 1,
`wherein said modifying a map is based on a characteristic of
`a class of images to be displayed.
`5. The method of image processing according to claim 1,
`wherein said modifying a map to increase a visibility of a
`characteristic of a displayed image includes:
`obtaining a characteristic of an imageto be displayed; and
`modifying the map according to the obtained characteris-
`tic.
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`17. The method of image processing according to claim 1,
`wherein said modifying a map to increase a visibility of a
`characteristic of a displayed image includes modifying the
`mapto increase a visibility of rounded shapes.
`18. The method of image processing according to claim 1,
`wherein the image signal is derived from a photographic
`representation of living tissue obtained using at least one
`among, a penetrating, radiation and a penetrating emission.
`19. The method of image processing according to claim 1,
`wherein the image signal is derived from an X-ray photo-
`graph.
`20. The method of image processing accordingto claim 1,
`said method comprising verifying that a desired structure was
`not removed from the map during said modifying.
`21. The method of image processing according to claim 20,
`wherein said verifying includes calculating, a difference
`6. The method of image processing according to claim 1,
`between the map and the modified map.
`wherein said modifying a map includes modifying the map
`22. The method of image processing according to claim 1,
`according to a desired frequency responseofthe display.
`wherein said modifying a map to increase a visibility of a
`7. The method of image processing according to claim 1,
`characteristic of a displayed image includes modifying the
`wherein said modifying a map includes modifying the map
`map accordingtoafirst selected characteristic inafirst region
`according to a desired response of the display to a predeter-
`ofthe display, and modifying the map according to a second
`mined image characteristic.
`selected characteristic in a second region of thedisplay,
`8. The method of image processing according to claim 1,
`wherein the first characteristic is different than the second
`wherein said modifying a map includesattenuating a magni-
`characteristic, and wherein the first region is separate
`tude of a first component ofthe maprelative to a magnitude of
`from the second region.
`a second componentof the map, wherein the second compo-
`23. The method ofimage processing according to claim 1,
`nent has a higher spatial frequency than thefirst component.
`said method comprising calculating a plurality of correction
`9. The method of image processing according to claim 8,
`functions based on the modified map.
`wherein said modifying a map includesattenuating a magni-
`tude ofa third componentofthe maprelative to the magnitude
`24. The method of image processing according to claim 23,
`wherein said obtaining a display signal comprises applying,
`of the second componentof the map, wherein the third com-
`toa value ofthe imagesignal that correspondsto a pixel ofthe
`ponent has a higher spatial frequency than the second com-
`ponent.
`display, a correction function that corresponds to the pixel
`from amongtheplurality of correction functions.
`10. The method of image processing according, to claim 1,
`25. The method of image processing according to claim 1,
`wherein said moditying a map to increase a visibility ofa
`wherein the map comprises a plurality of correction func-
`characteristic of a displayed image includes modifying the
`tions, each of the plurality of correction functions corre-
`mapto increase a visibility of an image area having a spatial
`spondingto at least one ofthe plurality of pixels.
`frequency greater than 0.1 cycles per degree.
`26. The method of image processing accordingto claim 25,
`11. The method of image processing according to claim 1,
`wherein said obtaining a display signal comprises applying,
`wherein said moditying a map to increase a visibility of a
`toa value ofthe imagesignal that correspondsto a pixel ofthe
`characteristic of a displayed image includes modifying the
`display, a correction function that corresponds to the pixel
`map to increase a perceptibility of features of a displayed
`from amongthe plurality of correction functions.
`image that are mutually separated by more than one arc-
`minute.
`27. The method of imageprocessing according to claim 1,
`wherein the luminance resolution of the display signal is
`greater than the luminanceresolution of the imagesignal.
`28. The method of image processing according to claim 1,
`wherein the luminance resolution of the display signal is
`greater than the luminanceresolution ofthe display.
`29. The method ofimage processing according to claim 28,
`said method comprising displaying the display signal on the
`display, said displaying including performing an error diffu-
`sion technique based on the display signal.
`30. The method of image processing according to claim 1,
`said method comprising attenuating a component of the
`image signal according to a characterization of noise of an
`imagedetector.
`31. The method ofimage processing according to claim 1,
`wherein said modifying a map includes modifying the map to
`reduce a visibility of a defective pixel of the display.
`32. A data storage medium having machine-readable
`instructions describing the method of image processing
`according to claim 1.
`33. ‘lhe method of image processing according to claim 1,
`wherein said method comprises using a correction circuit to
`perform said obtaining a display signal.
`
`13. The method of image processing according to claim 1,
`wherein said modifying a map to increase a visibility of a
`characteristic of a displayed image includes modifying the
`map according to a contrast sensitivity function.
`14. The method of image processing according to claim 1,
`wherein said modifying a map to increase a visibility of a
`characteristic of a displayed image includes modifying the
`map according to a predetermined featureofinterest.
`15. The method of image processing according to claim 1,
`wherein said modifying a map to increase a visibility of a
`characteristic of a displayed image includes modifying the
`mapto increase a visibility ofa clinically relevant feature.
`16. The method of image processing according to claim 1,
`wherein said modifying a map to increase a visibility of a
`characteristic of a displayed image includes modifying the
`map according to a shape and size of a clinically relevant
`feature.
`
`12. The method of image processing accordingto claim 1,
`wherein said modifying a map to increase a visibility of a
`characteristic of a displayed image includes modifying the
`map to increase a visibility of an area in accordance with a
`contrast of the area.
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`US 7,639,849 B2
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`33
`34. An image processing apparatus comprising:
`an array ofstorage elements configured to store, foreach of
`a plurality of pixels of a display, a measure of a light-
`output responseof at least a portion of the pixel at each
`of a plurality of driving levels; and
`an array of logic elements configured to modify a map
`based on the stored measures andto obtain, based on the
`modified map and an imagesignal that representsat least
`one physical and tangible object, a display signal that is
`configured to cause the display to depict the at least one
`physical and tangible object,
`whereinthe array of logic elements is configured to modify
`the map to increase a visibility of a characteristic of a
`displayed image during a use ofthe display.
`35. The image processing apparatus accordingto claim34,
`wherein said array oflogic elements is configured to attenuate
`a magnitude of a first component of the map relative to a
`magnitude of a second component of the map, wherein the
`second componenthas a higherspatial frequency thanthefirst
`component.
`36. A method of image processing, said method compris-
`ing:
`for each ofa plurality of pixels of a display, obtaining a
`measure ofa light-output responseofat least a portion of
`the pixel at each of a plurality of driving levels;
`modifying a map of the display that is based on the
`obtained measures, said modifying including, with
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`respect to a magnitude of a component havinga spatial
`period between one and fifty millimeters, decreasing a
`magnitude of a component having a spatial period less
`than one millimeter and decreasing a magnitude of a
`component having a spatial period greater than fifty
`millimeters; and
`based on the modified map and an image signal that rep-
`resents at least one physical and tangible object, obtain-
`ing a display signal that is configured to cause the dis-
`play to depict the at least one physical and tangible
`object.
`37.A method of image processing, said method compris-
`ing:
`for each of a plurality of pixels of a display, obtaining a
`measure of a luminanceofat least a portion of the pixel
`in response to each ofa plurality of different electrical
`driving levels;
`to increase a visibility of a characteristic of a displayed
`image during a use ofthe display, modifying a map that
`is based on the obtained measures; and
`based on the modified map and an image signal that rep-
`resents at least one physical and tangible object, obtain-
`ing a display signal that is configured to cause the dis-
`play to depict the at least one physical and tangible
`object.
`
`
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