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WO2006002327A2 - Systeme et procede d'analyse de l'augmentation de l'amplitude appropriee a des afficheurs a haut niveau de bits sur des systemes a bas niveau de bits, determination de l'epaisseur du materiau et visualisation en 3d des dimensions de l'espace couleur - Google Patents

Systeme et procede d'analyse de l'augmentation de l'amplitude appropriee a des afficheurs a haut niveau de bits sur des systemes a bas niveau de bits, determination de l'epaisseur du materiau et visualisation en 3d des dimensions de l'espace couleur Download PDF

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Publication number
WO2006002327A2
WO2006002327A2 PCT/US2005/022312 US2005022312W WO2006002327A2 WO 2006002327 A2 WO2006002327 A2 WO 2006002327A2 US 2005022312 W US2005022312 W US 2005022312W WO 2006002327 A2 WO2006002327 A2 WO 2006002327A2
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WIPO (PCT)
Prior art keywords
image
magnitude
bit level
grayscale
computer
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PCT/US2005/022312
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English (en)
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WO2006002327A3 (fr
Inventor
Wayne E. Ogren
Patrick B. Love
Peter B. Mclain
Rick Mancilla
Edward Steiner
William Paul Rogers
Andrew Haring
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Lumeniq, Inc.
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Priority to EP05763406A priority Critical patent/EP1766553A2/fr
Publication of WO2006002327A2 publication Critical patent/WO2006002327A2/fr
Publication of WO2006002327A3 publication Critical patent/WO2006002327A3/fr

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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/90—Dynamic range modification of images or parts thereof
    • G06T5/92—Dynamic range modification of images or parts thereof based on global image properties

Definitions

  • HVS perception of changes in grayscale tonal values is variable, affected by multiple factors.
  • "Just noticeable difference - JND” identifies HVS ability to distinguish minor differences of grayscale intensity for side-by-side samples, and is also known as the Weber Ratio.
  • a simple thought experiment exemplifies the variability of HVS perception, in this case, the variation of JND with overall luminance level.
  • the JND variability is quantified in DICOM Part 14( Figure 2): Grayscale Standard Display Function.
  • Electronic image processing is standardized per DICOM Part 14 to portray up to 1000 JND grayshades.
  • the HVS may be able to perceive as many as 1,000 tonal grayshades under properly controlled observation conditions, but as a topographic surface, the perception task is relieved of this need for sophisticated methods.
  • LumenlQ, Inc. (“Lumen”) has numerous patents and published patent applications that discuss methods, systems, etc., of using 3D visualization to improve a person's ability to see small differences in an image, such as small differences in the lightness or darkness (grayscale data) of a particular spot in a digital image.
  • these methods and systems display grayscale (or other desired intensity, etc.) data of a 2D digital image as a 3D topographic map: The relative darkness and lightness of the spots (pixels) in the image are determined, then the darker areas are shown as “mountains,” while lighter areas are shown as “valleys” (or vice-versa). In other words, at each pixel point in an image, grayscale values are measured, projected as a surface height (or z axis), and connected through image processing techniques.
  • Figures IA and IB show examples of this, where the relative darkness of the ink of two handwriting samples are shown in 3d with the darker areas shown as higher "mountains.”
  • HVS human visual system
  • the image can then be identified, rotated, flipped, tilted, etc.
  • Such images can be referred to as magnitude enhancement analysis images, although the kinematic (motion) aspect need only be present when desired (in which case the created representations are not truly kinematic images).
  • the methods and systems herein comprise analyzing industrial radiography (NDE) radiographs (or other scans, typically transmissive scans) with an analysis system able to distinguish very fine levels of grayness (image intensity), and correlating the image intensity to the actual thickness of the underlying material.
  • NDE industrial radiography
  • a thickness calibration function in the software can provide a 3D surface object that accurately matches the actual thickness of material in the 2D radiograph image. This allows rapid, interactive determination and visualization of material thickness. Other items can also be used to designate thickness variations, such as false-color representations.
  • RGB which stands for the standard red, green and blue channels for some color images
  • HSI which stands for hue, saturation, intensity for other color images.
  • the values of pixels measured along a single dimension or selected dimensions of the image color space to generate a surface map that correlates pixel value to surface height can be applied to color space dimensions beyond image intensity.
  • the methods and systems herein, including software can measure the red dimension (or channel) in an RGB color space, on a pixel-by-pixel basis, and generate a surface map that projects the relative values of the pixels.
  • the present innovation can measure image hue at each pixel point, and project the values as a surface height.
  • the height of a gridpoint on the z axis can be calculated using any function of the 2D data set representing the image or related in some meaningful way to the image.
  • an imaging modality such as MR or CT
  • another imaging modality such as PET or Nuclear Medicine
  • the gray scale at each grid point is derived from the first image, and the height is derived from the second image.
  • the software, etc. can contain a function g that maps a pixel in the 2D image to some other external variable (for example, Hounsfield units) and that value can then be used as the value for the z height (with optional adjustment).
  • the end result is a 3D topographic map of the Hounsfield units contained in the 2D image; the 3D map would be projected on the 2D image itself.
  • the present discussion includes methods of displaying a high bit level image on a low bit level display system.
  • the methods can comprise: a) providing an at least 2-dimensional high bit level digital image; b) subjecting the high bit level image to magnitude enhancement analysis such that at least one relative magnitude across at least a substantial portion of the print can be depicted in an additional dimension relative to the at least 2-dimensions to provide a magnitude enhanced image such that additional levels of magnitudes can be substantially more cognizable to a human eye compared to the 2- dimensional image without the magnitude enhancement analysis; c) displaying a selected portion of the enhanced image on a display can comprise a low bit level display system having a bit level display capability less than the bit level of the high bit level image; and, d) providing a moveable window configured to display the selected portion such that the window can move the selected portion among an overall range of the bit level information in the high bit level image.
  • the selected portion can comprise at least one bit level less information than the bit level of the high bit level image, and the high bit level image can be at least a 9 bit level image and the display system can be no more than an 8 bit level display system.
  • the high bit level image can be a 16 bit level image and the display system can be no more than an 8 bit level display system.
  • the image can be a can be a digital conversion of a photographic image, and the magnitude can be grayscale, and/or comprise at least one of hue, lightness, or saturation or a combination thereof.
  • the magnitude can comprise an average intensity defined by an area operator centered on a pixel within the image, and can be determined using a linear or non-linear function.
  • the magnitude enhancement analysis can be a dynamic magnitude enhancement analysis, which can comprise at least one of rolling, tilting or panning the image, and can comprise incorporating the dynamic analysis into a cine loop.
  • the discussion herein includes methods of determining and visualizing a thickness of a sample.
  • This can comprise: a) providing an at least 2- dimensional transmissive digital image of the sample; b) subjecting the image to magnitude enhancement analysis such that at least one relative magnitude across at least a substantial portion of the print can be depicted in an additional dimension relative to the at least 2-dimensions to provide a magnitude enhanced image such that additional levels of magnitudes can be substantially more cognizable to a human eye compared to the 2- dimensional image without the magnitude enhancement analysis; and c) comparing the magnitude enhanced image to a standard configured to indicate thickness of the sample, and therefrom determining the thickness of the sample.
  • the methods further can comprise obtaining the at least 2- dimensional transmissive digital image of the sample.
  • the standard can be a thickness reference block, and the sample can be substantially homogenous.
  • the thickness reference block and the sample can be of identical material, the thickness reference block can have thickness values to provide intermediate thickness values with respect to the object of interest, and can be located substantially adjacent to each other.
  • the discussion herein includes methods of displaying a color space dimension, comprising: a) providing an at least 2-dimensional digital image comprising a plurality of color space dimensions; b) subjecting the 2-dimensional digital image to magnitude enhancement analysis such that a relative magnitude for at least one color space dimension but less than all color space dimensions of the image is depicted in an additional dimension relative to the at least 2-dimensions to provide a magnitude enhanced image such that additional levels of magnitudes of the color space dimension are substantially more cognizable to a human eye compared to the 2-dimensional image without the magnitude enhancement analysis; c) displaying at least a selected portion of the magnitude enhanced image on a display; and, d) analyzing the magnitude enhanced image to determine at least one feature of the color space dimension that would not have been cognizable to a human eye without the magnitude enhancement analysis.
  • the methods further comprise determining an optical density of at least one object in the image, such as breast tissue.
  • the magnitude enhancement analysis is a dynamic magnitude enhancement analysis, and can comprise, if desired, dynamic analysis comprising at least rolling, tilting and panning the image.
  • the discussion herein includes computer-implemented programming that performs the automated elements of any of the methods herein, as well as computers comprising such computer-implemented programming.
  • the computer can comprise a distributed network of linked computers, can comprise a handheld and/or wireless computer.
  • the systems can also comprise a networked computer system comprising computer-implemented programming as above.
  • the networked computer system can comprise a handheld wireless computer, and the methods can be implemented on the handheld wireless computer.
  • the systems can also comprise a networked computer system comprising a computer as discussed herein.
  • a networked computer system comprising a computer as discussed herein.
  • Figures IA and IB show examples of magnitude enhancement analysis processing of two handwriting samples with the darker areas shown as higher "mountains.”
  • Figure 2 schematically depicts image perception as a system of scene, capture, processing, display, and observation processes.
  • Figure 3 schematically depicts an application of image perception processes for diagnostic and analytical decision making purposes improved by use of 3D surface mapping of image intensity data
  • Figure 4 schematically depicts interactive transformation of grayscale intensity to elevation using a Kodak grayscale.
  • the 3D surface image in the lower panel uses pseudocolor and perspective view in addition to mapping grayscale intensity to the z-axis. High bit level grayscale tonal information can thus be represented independent of human grayscale and display limitations.
  • Figure 5 schematically depicts a TG18-PQC test pattern for comparison of printed film and electronic display luminance conventional (left) and intensity surface display (right), no contrast adjustment.
  • Figure 6 schematically depicts a TG18-PQC test pattern for comparison of printed film and electronic display luminance conventional (left) and intensity surface display (right), with contrast adjustment.
  • Figure 7 schematically depicts a TG18-pqc test pattern for comparison of printed film and electronic display luminance magnitude enhancement analysis view of 3D surface, 65,536 grayscale Z-axis.
  • 3D surface image is composed of grayscale intensities 0 to 4096. Full range display identifies the grayscale intensity region of interest.
  • Figure 8 schematically depicts a TG18-PQC test pattern for comparison of printed film and electronic display luminance magnitude enhancement analysis view of 3D surface showing 65,536 grayscale Z-axis clipped to display grayscales 0 to 4096. Clipping of the Z-axis need not alter any of the grayscale data values or their contrast relationships.
  • Figure 9 depicts a screen capture of a computer-implemented system providing magnitude enhancement analysis and able to determine thickness values to provide intermediate thickness values with respect to an object of interest.
  • Figure 10 depicts a further screen capture of a computer-implemented system as in Figure 9.
  • Figure 11 depicts a further screen capture of a computer-implemented system as in Figure 9.
  • Figure 12 depicts a further screen capture of a computer-implemented system as in Figure 9.
  • Figure 13 depicts a further screen capture of a computer-implemented system as in Figure 9.
  • the present systems and methods provides approaches comprising magnitude enhancement analysis and configured to display intensity-related features of high-bit images, such as grayscale, on low-bit display systems, without distorting the underlying intensity unless desired, measuring the thickness of materials, and/or enhancing perception of saturation, hue, color channels and other color space dimensions in a digital image, and external datasets related to a 2d image.
  • HVS human eye
  • the capture and processing of grayscale in an image can be considered as 2 portions:
  • the display portion includes the image acquisition, film/data processing and the display of grayscale image intensities.
  • the display may be a variety of methods including CRT monitor, transparency film on a light box, printed hardcopy photographs, and more.
  • the display process is designed to portray an image judged by the observer to correctly represent the source scene.
  • the observation portion includes human observer perception of the grayscale image intensity display, subject to a wide variety of individualized perception limitations (e.g., age) and environmental surrounding factors (e.g., ambient lighting level).
  • HVS is highly adaptable to changes in luminous intensity
  • HVS is relatively poor at quantitatively identifying similar intensities separated by distances or by a few seconds of time.
  • HVS has poor ability to determine exact intensity values.
  • the conflict between limited grayscale display capabilities and the need for accurate reproduction of wide ranging grayscale scene image information can be treated with the innovative approaches herein.
  • the 3D surface construction relieves the image display equipment from the requirement of accurate grayscale tonal intensity reproduction, or the use of image processing to compress high dynamic range (HDR) intensities for display on low dynamic range (LDR) devices.
  • the methods and software, etc., herein address the challenging task of accurate display and perception of, e.g., JNDs or widely varying extremes of dynamic range in grayscale values.
  • extreme ranges include sunlight, bright lamp intensities, cave-like darkness, which can be mapped to the 3D surface representations herein and presented for observation.
  • the quality of image acquisition can be the limiting factor controlling the number of potential grayshades available for display and perception.
  • the systems, etc., herein comprise providing and using an interactive surface elevation (3d) representation that allows extremely small, as well as very large, changes in grayscale values to be mapped with high accuracy and detail definition.
  • the systems, etc. transform grayscale image intensity/film density to a 3D surface representation of the grayscale image intensity/film density, where grayscale tonal values are transformed into "elevation" shapes and forms corresponding to the grayscale value of the respective pixel.
  • the elevation shapes and forms can be represented at any chosen contrast levels or hues, avoiding grayscale tonal display and HVS perception issues.
  • the systems, etc. provide methods of displaying grayscale shades of more than 8 bits (more than 256 shades) and higher (16 bit, 65,536 grayscale for example) on conventional display equipment, typically capable of a maximum of 8 bit grayscale discrimination.
  • the Z-axis of a high bit level surface image can be assigned a scale factor consistent with the bit level of the image, such as 1024 for 10 bit image, 4096 for 12 bit image and so-on. In this way, the monitor or printer no longer needs to provide the 1024 or 4096 gray shades reproduction and discrimination ability, since the Z-axis dimension represents the gray shade as a unit of distance along the Z-axis.
  • the image can be viewed using interactive tools discussed elsewhere herein, for example, zooming and rotating for improved viewing perspectives.
  • An alternative processing scheme such as "windows" and "leveling" is provided.
  • the grayscale values exceeding the monitor's or printer's capability requires the analyst to adjust the output of the display using image processing tools.
  • a new portion of the overall grayscale will become visible at the expense of losing visibility of another portion of the grayscale.
  • the adjustment process uses the term “window” to discuss a subset of the overall grayscale range, 256 of 4096 for example. This "window” may be located to view grayscale values at midtone "level” (1920 to 2176), extremely dark “level” (0 to 255), or elsewhere along the 4096, 12 bit scale.
  • a 256 grayscale portion (window) of extremely dark (level) grayscales from the 4096 or other high bit level image would be adjusted to display those dark grayscales using midtone level grayscales readily visible to the HVS on common display equipment, otherwise the balance of 3840+ grayscales (4096 minus 256) in the 12 bit image would generally not be visible on the display to the human eye, and possibly not distinguished by the display itself.
  • the extremely dark shades are visible without adjustment (window and level), as well as the midtone and extremely light shades of gray. All 4096 grayscale values will be available for HVS perception (or more, if desired) as 3D surface object.
  • Printing devices have limited grayscale reproduction capability as well.
  • Grayscale visual perception illusions are the result of human visual perception systems performing adjustments to an image to match our a priori knowledge of the image (e.g., checkerboard illusion), enhancing edges for improved detection (e.g., mach bands), and other low and high order vision processes.
  • the following provides an example, including supporting discussion, of high bit display on low bit display systems. Presentation of a scene image for human perception involves a process of transformations that can be as illustrated in Figure 2.
  • Scene The range of luminous intensities which exist in a scene can be extremely large, exceeding the intensity variations perceived by human visual adaptation. HVS adaptation given sufficient time can exceed 100 million to 1 ratio (10 9 , starlight to bright daylight). The range of scene intensities can also be very low, such as a monotone painted wall, with very subtle intensity variations. 2. Capture Device - Typical photographic intensity ratio capture is less than 10,000 to 1 (10 4 ) maximum. Capture limitations are technical/hardware related, such that high quality, medical/scientific/military devices capture a greater dynamic range and store the information as high bit level data. High bit level data is common with high quality devices, while consumer/office quality digital capture devices default to 8 bit grayscale resolution.
  • the processes, etc., herein can be employed, for example, at the image processing steps, image display and HVS observation steps 3, 4, and 5 in Figure 2.
  • the processes, etc. transform the image from a grayscale tonal or luminance reproduction to a 3D surface as shown by the lower "path" in Figure 3.
  • the 3D surface representation as compared to conventional 2D methods is illustrated in Figure 3 for the example of a chest X-ray image.
  • the full dynamic range obtained at the image capture stage can be retained and displayed to the observer free of the image processing, display and perception constraints of the conventional grayscale intensity representation method (upper "path" of Figure 3).
  • Application of the 3D surface method can utilize image data as it exists prior to conventional image processing methods of brightness and contrast adjustment or dynamic range compression.
  • the processes transform the 2D grayscale tonal image to 3D by "elevating” (or depressing, or otherwise “moving") each desired pixel of the image to a level proportional to the grayscale tonal value of that pixel in its' 2D form.
  • the pixel elevations can be correlated 1:1 corresponding to the grayscale variation, or the elevations can be modified to correlate 10:1, 5:1, 2:1, 1:2, 1:5, 1:10, 1:20 or otherwise as desired.
  • the methods can also be applied to image features other than grayscale, such as hue and saturation; the methods, etc., herein are discussed regarding grayscale for convenience.
  • the ratios can also be varying such that given levels of darkness or lightness have one ratio while others have other ratios, or can otherwise be varied as desired to enhance the interpretation of the images in question. Where the ratio is known, measurement of grayscale intensity values on a spatial scale (linear, logarithmic, etc.) becomes readily practical using conventional spatial measurement methods, such as distance scales or rulers.
  • the pixel elevations are typically connected by a surface composed of an array of small triangular shapes (or other desired geometrical or other shapes) interconnecting the pixel elevation values.
  • each triangle abuts the edges of adjacent triangles, the whole of which takes on the appearance of a surface with elevation variations.
  • the grayscale intensity of the original image resembles a topographic map of terrain, where higher (mountainous) elevations could represent high image intensity, or density values.
  • the lower elevations (canyon-lands) could represent the low image intensity or density values.
  • the use of a Z-axis dimension allows that Z-axis dimension to be scaled to the number of grayscale shades inherently present in the image data. This method allows an unlimited number of scale divisions to be applied to the Z-axis of the 3D surface, exceeding the typical 256 divisions (gray shades) present in most conventional images.
  • High bit level, high grayscale resolution, high dynamic range image intensity values can be mapped onto the 3D surface using scales with 8 bit (256 shades), 9 bit (512 shades), 10 bit (1,024 shades) and higher (e.g., 16 bit, 65,536 shades).
  • the image representation can utilize aids to discrimination of elevation values, such as isopleths (topographic contour lines), pseudo-colors assigned to elevation values, increasing/decreasing elevation proportionality to horizontal dimensions (stretching), fill and drain effects (visible/invisible) to explore topographic forms, and more.
  • Figure 4 illustrates a 3D surface method of mapping image intensity using a standard reference object.
  • the exemplary object is the Kodak grayscale Q-13, Catalog number 152 7654, a paper-based grayscale target for quality control of photographic images.
  • the dynamic range of grayscale is from 0.05 density to 1.95 in 20 density steps of 0.10 density increments. This scale closely matches photographic grayscale reproduction range capability.
  • the observer will note the darkest grayscale targets will appear to be very similar to one another. The dark shades appear very similar, despite the fact that density increments vary by the constant value of 0.10 units between them.
  • the elevation dimension can be used to discriminate between these very similar shades, as well as use of pseudo-color mapping as shown in Figure 4.
  • the Kodak target is a low dynamic range object, representative of grayscale range reproducible with photographic methods.
  • High dynamic range images with many times darker and brighter regions can also be accurately reproduced using the systems, etc., herein. As an elevation map, these dark and bright shades can be readily observable as shapes corresponding to that grayscale value.
  • High bit level images shown as a 3D surface can accurately portray grayscale intensity information that greatly exceeds display device ability to accurately reproduce HDR grayscale intensity tonal values. Transformation of extreme (and subtle) gray shades to a 3 dimensional surface as discussed herein provides spatial objects for detection by HVS, and for display devices.
  • Figure 5 is a side-by-side comparison of a test pattern image available from the American Association of Physicists in Medicine, Task Group 18 (AAPM TGl 8: American Association of Physicists in Medicine Task Group 18 http://deckard.mc.duke.edu/ ⁇ samei/tgl8).
  • the 16 bit image (TG18-PQC Test Pattern for Comparison of Printed Film and Electronic Display Luminance) is shown on the left side as it would normally appear on a conventional electronic display.
  • On the right hand side is the image as it appears using the methods herein, a 3D surface elevation object rotated to show the resulting surface shape.
  • Figure 7 illustrates the same image as Figure 5, with no contrast adjustments, full grayscale range of 0 to 65,536.
  • the Z-axis projects out of the field of view in this case, since the image is a test pattern for radiographic displays.
  • the software interface is shown to illustrate certain tools available for further image data evaluation actions.
  • Figure 8 is the same image data with the Z-axis "clipped" via a viewing window to the grayscale region of interest (0 to 4096), boosting 3d surface visibility without alteration to the image dataset.
  • the systems and software herein can indicate corrosion, defects or other artifacts in a an imaged, e.g., radiographed, object.
  • Review of industrial images shows that the software, by accurately measuring and projecting/displaying minute variations in radiographic image grayscale values, can provide NDE analysts with tools to accurately measure the thickness of the underlying image.
  • Exemplary methodology as applied to industrial images can be as follows: [00063] 1. The thickness of material in the radiographic image directly modulates or attenuates radiation (or other transmissive scanning mechanism) passing through the material.
  • Radiation reaching the film or digital sensor interacts with the film or sensor to provide a grayscale tonal image corresponding to the radiation exposure level.
  • the grayscale tonal value can be calibrated by use of a thickness reference block, so that an accurately dimensioned Z-axis, or thickness dimension, is presented in the 3D surface image.
  • Certain mathematical correction factors can be built into the imaging software to correct for possible distortions caused by radiation physics.
  • the software Once the radiograph is in digital format (either through scanning of physical film, or through direct digital capture, or otherwise as desired), the software herein measures the grayscale variations and projects them as a 3D surface. In rendering the surface, the software can incorporate algorithms to correct for any distortions created by radiation physics. Surface elevation variations in the image will correspond to actual thickness of the material in the radiograph image.
  • IQIs Image Quality Indicators
  • ASTM American Society of Testing and Materials
  • ASME American Society of Mechanical Engineers
  • step wedge thickness blocks can be included for reference to grayscale intensity versus thickness.
  • known step wedge thickness values or other comparison standards can be depicted in the software corresponding to the grayscale value of that target region of the image.
  • Multiple step wedge thickness regions, covering the thickness range of the material in the image, can be entered as calibration values into the software.
  • grayscale values depicted as a 3D surface in the software and actual thickness values can be co-related to one another (calibrated).
  • the software can dimension the grayscale intensity axis (Z-axis) with incremental values of thickness (inches, millimeters, and similar).
  • the radiographic grayscale intensity image can be represented as a 3D surface, where peaks and valleys of Z-axis "elevation" will correspond to shadows and highlights (or vice versa), for example.
  • an object of known thickness e.g., step wedge
  • an object of known thickness e.g., step wedge
  • normal radiographic procedures can be applied if desired.
  • large areas of the radiographic image can accurately portray the object thickness.
  • Correction factors taking into account the geometric arrangement of point source radiation, object being radiographed, and the radiation sensor/detector producing the image can be included in the calibration, software or otherwise, of image intensity to material thickness.
  • these methods, systems, etc. provide for area-wide measurement of the thickness of homogenous material (or other suitable material) using conventional radiographic image acquisition, hi one embodiment of carrying this out, ASTM and ASME radiographic requirements include the use of IQI as well as step wedge reference objects.
  • Use of step wedge object(s) in the radiographic image field of view provides a suitable reference object, if needed, for grayscale versus thickness calibration using the software interface. Along with geometric correction factors, the reference object is used to calibrate, or quantify thickness in the entire field of view.
  • conventional practice requires manual use of a densitometer instrument as the step wedge and an individual location in the image to provide a thickness measurement at that point.
  • each additional point of thickness measurement requires repetition of the measurement process.
  • the end result is a tabulation of measurements data, as compared to a 3D surface image representation of object thickness.
  • the image rendered in the software of the present innovations is quantitatively accurate for thickness, and the software interactivity provides statistical, area-wide, as well as point specific thickness information.
  • the systems, etc. provide improved effectiveness of thickness evaluations based upon radiographic methods of scanning a substrate then viewing it or analyzing it using the methods herein.
  • the thickness measurement methods may be applied to digitized film images as well as digital radiographic methods.
  • the method provides a common mode means of thickness determination regardless of radiographic method or image type.
  • the following paragraphs discuss an exemplary thickness measurement work flow process. [00074] 1.
  • the image can have a suitable thickness reference object in the field of view (e.g., a step wedge).
  • the reference object properties can: a. be identical material to object of interest, b. have thickness values to provide intermediate thickness values with respect to the object of interest, c. be located adjacent to object of interest.
  • 3. Typically, if the image is a film radiograph, convert the film by electronic image scanning or other desired procedure to provide a digital file. If the image is a direct digital radiograph, no additional conversion may be desired.
  • each subsection of the grayscale target has a known thickness value by design and construction of the target (step wedge). Using the mouse to select each subsection (one at a time) and then clicking "Take Sample” produces the following result.
  • the numbered numerical value under "calibrated value” is the actual material thickness value entered by the operator for the sampled portion of the grayscale target (step wedge). This and certain other steps can be automated, if desired.
  • repetition of this procedure can sample additional regions of the grayscale target until completely sampled.
  • the "Calibrate” button is clicked, resulting in adjustment of the Z-axis to reflect the thickness values entered numerically.
  • RGB which stands for the standard red, green and blue channels for some color images
  • HSI which stands for hue, saturation, intensity for other color images.
  • RGB red, green and blue channels
  • HSI hue, saturation, intensity for other color images.
  • RGB red, green and blue channels
  • HSI hue, saturation, intensity for other color images.
  • RGB red, green and blue channels
  • HSI hue, saturation, intensity for other color images.
  • color spaces can be converted from one to another; if digital image pixels are encoded in RGB, there are standard lossless algorithms to convert the encoding format from RGB to HSI.
  • the values of pixels measured along a single dimension or selected dimensions of the image color space to generate a surface map that correlates pixel value to surface height can be applied to color space dimensions beyond image intensity.
  • the methods and systems herein, including software can measure the red dimension (or channel) in an RGB color space, on a pixel-by-pixel basis, and generate a surface map that projects the relative values of the pixels.
  • the present innovation can measure image hue at each pixel point, and project the values as a surface height.
  • the pixel-by-pixel surface projections can be connected through image processing techniques (such as the ones discussed above for grayscale visualization technology) to create a continuous surface map.
  • the image processing techniques used to connect the projections and create a surface include mapping 2D pixels to grid points on a 3D mesh (e.g., triangular or rectilinear), setting the z axis value of the grid point to the appropriate value (elevating based on the selected metric, e.g., intensity, red channel, etc.), filling the mesh with standard 3D shading techniques (gouraud, flat, etc) and then lighting the 3D scene with ambient and directional lighting.
  • 3D shading techniques can be implemented for such embodiments using modifications in Lumen's grayscale visualization software, as discussed in certain of the patents, publications and applications cited above.
  • any dimension, or weighted combination of dimensions in a 2D digital image can be represented as a 3D surface map.
  • Other examples include conversion of the default color space for an image into the HLS (hue, lightness, saturation) color space and then selecting the saturation or hue, or lightness dimensions as the source of surface height. Converting to an RGB color space allows selection of color channels (red channel, green channel, blue channel, etc.). The selection can also be of single wavelengths or wavelengths bands, or of a plurality of wavelengths or wavelength bands, which wavelengths may or may not be adjacent to each other.
  • selecting and/or deselecting certain wavelength bands can permit detection of fluorescence in an image, detect the relative oxygen content of hemoglobin in an image, or breast density in mammography.
  • the height of each pixel on the surface can be calculated from a combination of color space dimensions (channels) with some weighting factor (e.g., 0.5 * red + 0.25 * green + 0.25 * blue), or even combinations of dimensions from different color spaces simultaneously (e.g., the multiplication of the pixel's intensity (from the HSI color space) with its luminance (from the YUV color space)).
  • the present innovations can display 3D topographic maps or other 3D displays of color space dimensions in images that are 1 bit or higher.
  • variations in hue in a 12 bit image can be represented as a 3D surface with 4,096 variations in surface height.
  • the methods, systems, etc. are directed to enhanced perception of related datasets.
  • the height of a gridpoint on the z axis can be calculated using any function of the 2D data set.
  • the external function or dataset is related in some meaningful way to the image.
  • the software, etc. can contain a function g that maps a pixel in the 2D image to some other external variable (for example, Hounsfield units) and that value can then be used as the value for the z height (with optional adjustment).
  • a function g that maps a pixel in the 2D image to some other external variable (for example, Hounsfield units) and that value can then be used as the value for the z height (with optional adjustment).
  • the end result is a 3D topographic map of the Hounsfield units contained in the 2D image; the 3D map would be projected on the 2D image itself.

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Image Processing (AREA)
  • Image Generation (AREA)

Abstract

L'invention porte sur des systèmes et sur des procédés consistant à analyser l'augmentation de l'amplitude et configurés pour afficher des caractéristiques d'intensité des images à haut niveau de bits, telles que l'échelle de gris, sur des systèmes d'affichage à bas niveau de bits, sans déformer l'intensité sous-jacente sauf si cela est désiré; mesurer l'épaisseur des matériaux et/ou renforcer la perception des canaux de saturation, teinte, couleur et autres dimensions spatiales dans une image numérique, et afficher des ensembles de données extérieurs liés à une image 2D. Les divers modes de mise en oeuvre et formes d'exécution de l'invention permettent d'améliorer des systèmes et des méthodes d'affichage et d'analyse, notamment par l'oeil humain (système visuel humain).
PCT/US2005/022312 2004-06-23 2005-06-23 Systeme et procede d'analyse de l'augmentation de l'amplitude appropriee a des afficheurs a haut niveau de bits sur des systemes a bas niveau de bits, determination de l'epaisseur du materiau et visualisation en 3d des dimensions de l'espace couleur WO2006002327A2 (fr)

Priority Applications (1)

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EP05763406A EP1766553A2 (fr) 2004-06-23 2005-06-23 Systeme et procede d'analyse de l'augmentation de l'amplitude appropriee a des afficheurs a haut niveau de bits sur des systemes a bas niveau de bits, determination de l'epaisseur du materiau et visualisation en 3d des dimensions de l'espace couleur

Applications Claiming Priority (12)

Application Number Priority Date Filing Date Title
US58241404P 2004-06-23 2004-06-23
US60/582,414 2004-06-23
US58505904P 2004-07-02 2004-07-02
US60/585,059 2004-07-02
US60409204P 2004-08-23 2004-08-23
US60/604,092 2004-08-23
US61827604P 2004-10-12 2004-10-12
US60/618,276 2004-10-12
US63082404P 2004-11-23 2004-11-23
US60/630,824 2004-11-23
US66596705P 2005-03-28 2005-03-28
US60/665,967 2005-03-28

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WO2006002327A2 true WO2006002327A2 (fr) 2006-01-05
WO2006002327A3 WO2006002327A3 (fr) 2009-04-16

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US7116806B2 (en) * 2003-10-23 2006-10-03 Lumeniq, Inc. Systems and methods relating to AFIS recognition, extraction, and 3-D analysis strategies

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