WO1999026199A1 - Amelioration d'image a large bande - Google Patents

Amelioration d'image a large bande Download PDF

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Publication number
WO1999026199A1
WO1999026199A1 PCT/US1998/023933 US9823933W WO9926199A1 WO 1999026199 A1 WO1999026199 A1 WO 1999026199A1 US 9823933 W US9823933 W US 9823933W WO 9926199 A1 WO9926199 A1 WO 9926199A1
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WO
WIPO (PCT)
Prior art keywords
image
obtaining
features
function
luminance
Prior art date
Application number
PCT/US1998/023933
Other languages
English (en)
Inventor
Eliezer Peli
Original Assignee
Schepens Eye Research Institute, Inc.
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Schepens Eye Research Institute, Inc. filed Critical Schepens Eye Research Institute, Inc.
Priority to AU13155/99A priority Critical patent/AU1315599A/en
Priority to US09/234,846 priority patent/US6611618B1/en
Publication of WO1999026199A1 publication Critical patent/WO1999026199A1/fr
Priority to US10/619,124 priority patent/US7280704B2/en

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Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/50—Image enhancement or restoration using two or more images, e.g. averaging or subtraction

Definitions

  • This invention relates to methods and apparatus for image processing and more particularly to image enhancement.
  • the invention relates to methods and apparatus for the enhancement of both video images of natural scenes that contain a wide range of spatial frequencies and of real-world views of natural scenes.
  • This technique fails to capture the low frequency components that arise as a result of features that have significant variations in luminance mainly over an area larger than an 8 x 8 section. Therefore, such traditional image enhancement techniques are not suitable for enhancing the images of many natural scenes that contain a wide range of spatial frequencies. Further, human observers detect moving objects that contain a wide band of frequencies more readily than those with a narrow band of frequencies. Thus, the traditional techniques are not appropriate in systems for assisting detection of moving objects, or in systems that provide real-time viewing enhancement of natural scenes.
  • the methods and apparatus according to this invention modify an image by 1) locating certain features of the image, such as the boundaries of objects in the image, 2) manipulating such located features to obtain modified features, and 3) adding the modified features to the original image.
  • such practices of the invention employ a two-dimensional Hilbert transform of the image data to create a two- dimensional function, the so-called energy function, whose local maxima correspond to points lying on the boundaries between regions of marked difference in luminance, i.e., edges, or to points corresponding to peaks or troughs in luminance, i.e., bars.
  • the invention further provides techniques to interconnect these maxima, thus delineating the desired features.
  • An application of this invention is to improve the visibility of video images for people with visual impairment, e.g., cataracts or macular degeneration.
  • one embodiment of the present invention allows real-time image processing and enhancement of the real -world view for the visually impaired.
  • This embodiment incorporates a dedicated microprocessor, programmed to extract the boundaries of objects in the field of view, according to the methods of the invention from the data inputted from a digital camera.
  • This embodiment also incorporates video equipment to project the extracted features onto screens. These screens can be integrated in a wearable real-time image enhancement apparatus.
  • Another application enhances the real-world view, under reduced visibility conditions such as fog, by projecting the enhanced features, obtained from non-visual sensors, e.g., infrared or radar, on heads-up displays (HUD) of an airplane or of a car windshield.
  • HUD heads-up displays
  • Another application of this invention is to improve the visibility of television images for individuals with visual impairment.
  • other applications relate to the enhancement of satellite and reconnaissance pictures or other military imaging devices, and to the delineation of features of interest in such pictures.
  • the invention is typically practiced on a digital image that consists of a discrete two-dimensional map of luminance. Some embodiments of the invention represent such images by two dimensional matrices.
  • the invention employs an extension of the well known methods for calculating the Hilbert transform of a function in one dimension to obtain a discrete two-dimensional Hilbert transform of a function of the image data.
  • the one-dimensional Hilbert transform of a function of a single variable can be calculated by 1) obtaining the Fourier transform of the function, 2) obtaining a modified transform function whose values are zero at points where its independent variable is less than zero, and whose values are those of the Fourier transform at points where its independent variable is larger than zero.
  • a third step is to obtain the inverse transform of this modified transform function.
  • One preferred embodiment of the invention obtains the two-dimensional Hilbert transform of the image data by 1) computing the two-dimensional Fourier transform of the image, 2) obtaining a new two-dimensional transform function whose values in a selected arbitrary contiguous half of the two-dimensional Fourier plane are zero, and whose values correspond to those of the two-dimensional Fourier transform of the image in the other half, and 3) obtaining the inverse Fourier transform of the modified transform function.
  • the real part of the complex inverse Fourier transform of the modified transform function corresponds to the original image and the imaginary part corresponds to the Hilbert transform of the image.
  • a preferred embodiment of the invention combines the image data with the
  • the procedure for forming the energy function calls for obtaining the square root of the Pythagorean sum of the image data and of the values of the Hilbert transform at each point, e.g., at each pixel of a digital image.
  • One embodiment of the invention utilizes the positions of the peaks of the energy function to locate the strong luminance features of the image. It is understood that such peaks correspond to peaks or troughs in luminance, or to those locations in the original image where changes in image intensity profile occur because of the existence of maximal phase congruency among the various Fourier components of the image.
  • the local maxima of the energy function correspond to points of both minimum and of maximum intensity in the original image data, and also to the boundaries between regions of low and of high luminance. It is not reasonably feasible to classify the maxima of the energy function with respect to the polarity of the corresponding points in the image data based purely on the energy function. Thus, some embodiments of the invention implement a further examination of the image data at each point that corresponds to a maximum of the energy function to label the polarity of each such maximum.
  • One aspect of the present invention relates to the creation of a map of dots corresponding to the points designated as the maxima of the energy function.
  • the invention employs methods known in the art to connect these dots to produce lines corresponding to the desired features.
  • the invention provides the capability of manipulating these lines by widening them through convolution with an appropriate windowing function, e.g., a Gaussian with a selected width, or enhancing their intensities, to improve the contrast of the image.
  • Some embodiments of the invention employ only one arbitrarily selected polarity, i.e., either dark or bright, to display the dots or the contour lines at edges, whereas other embodiments utilize two polarities.
  • a bipolar representation displays an edge with two dots, one dark and the other bright, next to each other.
  • Some embodiments that utilize a bipolar representation examine the unmodified image to select a choice for juxtaposition of the dark and bright dots that corresponds to the sense of the transition of luminance at the corresponding location of the image. Both embodiments represent the polarity of bars in accordance with the polarity in the original image.
  • Other embodiments of the invention use only a single polarity of dots, i.e., light or dark, to represent all bars or edges.
  • a preferred embodiment of the invention superimposes these modified contour lines onto the original image to obtain a new image in which certain features have been modified, e.g., the boundaries of the objects in the image have been enhanced.
  • the invention can also enhance color images. Because the invention manipulates only a limited number of pixels, i.e., those corresponding to the strong features of the image, only a few pixels change color due to the enhancement. Thus, the methods of the invention are more efficient in enhancing color pictures than traditional techniques. Thus, the invention attains the objectives set forth above by extracting strong features of an image, manipulating these features to obtain modified features, and superimposing such modified features onto the original image to obtain a modified image.
  • FIGURE 1 is a flow chart depicting steps according to one embodiment of the invention for enhancing a wide-band image
  • FIGURE 2 illustrates examples of the application of the methods depicted in figure 1 to two images with both the unipolar and bipolar representations of edges
  • FIGURE 3 provides examples of the application of two alternative embodiments of the invention, where one embodiment employs two Hilbert transforms and the other employs four such transforms,
  • FIGURE 4 shows a flow chart depicting an apparatus according to an embodiment of the invention
  • FIGURE 5 shows a human observer employing an apparatus according to an embodiment of the invention for the real-time viewing enhancement of natural scenes
  • FIGURE 6 shows an original image and three enhanced versions of the original image obtained according to an embodiment of the invention, where the image labeled "enhanced” employs both dark and bright lines, and the other two modified images employ only bright lines,
  • FIGURE 7 shows an one embodiment of the invention for illuminating the features of an object in a natural scene
  • FIGURE 8 illustrates enhancement of images with different sizes according to the invention
  • FIGURE 9 similar to figure 8, shows the enhancement of two images with different sizes according to an embodiment of the invention.
  • FIGURE 10 depicts various steps according to one embodiment of the invention for enhancing broadcast television images. Illustrated embodiments
  • the flow chart of FIGURE 1 shows various steps that an illustrated embodiment of the invention employs to modify an image represented by Image Data.
  • This particular illustrated embodiment in step 10 applies a high pass filter in the spatial frequency domain to the image data to eliminate selected frequency components of the image.
  • the high pass filter is typically constructed to retain frequency components that correspond to a few cycles per image, e.g., 16 cycles per image or higher, and to discard components that correspond to lower frequencies.
  • the illustrated embodiment of FIGURE 1 obtains the two-dimensional Hilbert transform of the filtered image data in step 12 by performing a sequence of three operations.
  • the first operation is to calculate the two-dimensional Fourier transform of the filtered image data to obtain a transform function.
  • the second operation is to create a modified transform function that vanishes over a selected contiguous half of the two- dimensional Fourier space of the transformed filtered image data, and has values identical to those of the transform function of the previous operation in the other half.
  • the third operation is to apply an inverse Fourier transform to the modified transform function to obtain a complex function whose imaginary part corresponds to the Hilbert transform of the filtered image data.
  • An alternative practice of the operations of step 12 of the figure 1 sequence suited for manipulating an image data that is represented by a two-dimensional matrix, obtains a discrete two-dimensional Hilbert transform of the image data by performing three operations.
  • the first operation is to calculate a discrete two-dimensional Fourier transform of the image matrix to obtain a transform matrix.
  • the second operation is to set the values of a selected half of the components of the transform matrix to zero to obtain a modified transform matrix
  • the third operation is to obtain the discrete inverse Fourier transform of the modified matrix to obtain a matrix whose imaginary part corresponds to the discrete Hilbert transform.
  • One preferred embodiment of the invention sets the lower half of the transform matrix to zero to obtain the modified transform matrix.
  • Another embodiment sets the upper half of the transform matrix to zero to obtain the modified transform matrix.
  • another embodiment sets the components below the diagonal of the matrix to zero and retains the rest.
  • application of a discrete inverse Fourier transform to the modified transform matrix results in obtaining a matrix of complex numbers, the inverse modified transform matrix, whose imaginary part corresponds to the discrete Hilbert transform of the filtered image data.
  • FIGURE 1 shows that the step 14 of the illustrated embodiment constructs a so-called energy matrix by performing four operations that combine the image matrix with the discrete Hilbert transform, represented by the imaginary part of the modified transform matrix.
  • the first operation is to obtain the square of the image matrix.
  • the second operation is to obtain the square of the discrete Hilbert transform matrix.
  • the third operation is to add the square of each matrix to the square of the other, and the fourth operation is to compute the square root of the summation to obtain the energy matrix.
  • the same sequence of operations provides an energy function when applied to continuous functions rather than to discrete representations of such functions by matrices.
  • the peakfinder step 16 of the illustrated embodiment provides a number of maximum points of the energy matrix to subsequent steps of the illustrated embodiment by performing three operations.
  • the first operation locates the local extrema of the energy matrix, i.e., local maxima and minima, by computing a two- dimensional gradient of the energy matrix and finding points at which the gradient vanishes, according to known methods in the art.
  • the second operation obtains the second derivative of the energy matrix at each located extremum, to determine whether such a point corresponds to a maximum or a minimum of the energy matrix, and retains the maximum points and discards the minimum points.
  • the third operation compares the intensity of the maxima of the energy matrix or the intensity of the second derivative of the energy matrix at each selected maximum with a pre-defined threshold value, and retains only points whose intensities exceed the threshold value.
  • the maxima that the peakfinder step selects correspond to three types of features in the original image. They can either indicate the locations of minimum or maximum intensities, i.e., bars, or transitions between regions of varying intensities, i.e., edges. In the case of edges, the polarity of the transitions for a pre-defined direction, e.g., left to right and top to bottom, can not be readily gleaned from the energy matrix.
  • One implementation of the illustrated embodiment chooses an arbitrary unipolar representation of the located maxima, i.e., it represents the maxima as bright or dark dots regardless of whether they correspond to bars or edges and also regardless of their actual polarities.
  • Another implementation that opts for a bipolar representation employs dark and bright dots, symmetrically disposed with respect to the locations of the maxima, to display the maxima.
  • One such implementation chooses an arbitrary polarity for displaying the dark and bright dots that represent edges, whereas a different implementation examines the image data to choose a polarity that corresponds to that in the image.
  • FIGURE 1 shows that step 18 of the illustrated embodiment, the phase detector step, provides the option of examining the image data in a selected neighborhood of each point corresponding to a maximum of the energy matrix to determine whether such a point corresponds to a bar or an edge in the image. In addition, this step determines polarities of the transitions in luminance at points corresponding to edges in the image.
  • step 20 of the illustrated embodiment utilizes the information that the step 16 supplies, and also in some implementations the information that the step 18 supplies, to create contour lines corresponding to the selected strong luminance features of the image by performing three operations.
  • the first operation creates a two-dimensional map of dots corresponding to the selected maxima.
  • the second operation which is optional, can alter the widths of the dots through convolution with a tapered window, e.g., a Gaussian function with a pre-determined width, or alternatively enhance the dots by changing the degree of their luminance.
  • the third operation is to join the dots to create contour lines in a manner known in the art.
  • step 22 superimposes a display of the contour lines onto the original image.
  • the display can be unipolar or bipolar, and it can have an arbitrary polarity or a polarity that corresponds to that of the feature in the actual image.
  • steps 10 through 22 of FIGURE 1 produces an enhanced version of the original image by accentuating the strong luminance features of the image.
  • FIGURE 2 illustrates the results of the application of the methods of the embodiment illustrated in FIGURE 1 to two images.
  • the different views in FIGURE 2 allow the comparison of unipolar and bipolar edge representations of the modified images.
  • reference to views 2E and 2F shows that both the unipolar and bipolar displays represent the wrinkles on the forehead, i.e., bars, as dark lines.
  • the views 2B and 2E show that the unipolar displays represent edges, such as transitions in luminance at the boundary of the jacket and the face, as dark lines whereas the views 2C and 2F show that bipolar displays represent such transitions as dark and bright line pairs disposed symmetrically with respect to the center of the transition.
  • FIG. 1 a comparison of the bipolar edge representations in views 2C and 2F with the views 2 A and 2D of the unmodified images readily illustrates that the chosen polarities of the edges correspond to the actual polarities in the unmodified images.
  • Another embodiment of the invention combines multiple Hilbert transforms, obtained in the manner described in the illustrated embodiment of FIGURE 1, to produce a modified energy function of the filtered image.
  • this embodiment employs two sets of Hilbert transforms corresponding to two different orientations of axes in the Fourier plane to obtain a modified energy matrix.
  • the embodiment employs this modified energy matrix to delineate the selected features of the image in the same manner as described in the previous embodiment.
  • FIGURE 1 shows that the contour construction step 20 creates contours of all features obtained through multiple Hilbert transforms.
  • the image constructor step 22 superimposes all these contours onto the original image to produce an enhanced image.
  • One advantage of employing multiple Hilbert transforms is that each transform results in a preferential delineation of the luminance features that substantially lie in the direction of the selected axes in the two-dimensional Fourier plane, utilized to obtain the transform.
  • superposition of luminance features obtained from a set of Hilbert transforms results in better enhancement of the image than superposition of features obtained from only one such transform.
  • FIGURE 3 provides a comparison of two enhanced versions of an image obtained by employing multiple Hilbert transforms.
  • the view 2B of the original image 2A was obtained by employing two Hilbert transforms
  • the view 2D of the original image 2C was obtained by employing four Hilbert transforms.
  • FIGURE 4 depicts an apparatus according to an embodiment of the invention.
  • a digitizer 24 supplies a digitized image data corresponding to an input image to a microprocessor or a programmed digital computer 26.
  • the microprocessor or the computer performs a sequence of operations corresponding to the steps of the illustrated embodiment of FIGURE 1 on the digitized inputted image data to obtain data corresponding to an enhanced version of the input image.
  • FIGURE 5 shows an illustrated embodiment of the invention according to the apparatus of FIGURE 4 that allows real-time image enhancement of real- world scenery.
  • FIGURE 4 shows a human observer wearing an apparatus according to the invention that includes a video camera, preferably a digital camera, that provides image data corresponding to the natural scene. Subsequently, the apparatus transfers the digital image data to a dedicated microprocessor, programmed to extract the bars and edges in the image and to provide a contour map of the extracted bars and edges according to the methods of the present invention.
  • the processor transfers the contour map to a video display module that projects the map on two partially transparent screens positioned in the front of the observer's eyes, known in the art as a see-through head-mounted display. This allows the observer to view the natural scene with an enhancement of its distinctive features.
  • FIGURE 5 can also be designed to enhance a portion of an observer's field of view, e.g., the central portion.
  • Such an apparatus continuously enhances the central portion of the observer's field of view as the observer turns turn his eyes from one part of a natural scene to another
  • FIGURE 6 depicts various modified versions of a natural scene, employing different polarities, according to the methods of the present invention.
  • the image labeled enhanced uses a bipolar representation.
  • the bottom images use only positive polarities, i.e., bright lines.
  • the use of bright lines is the practical method for enhancing the real world view. While the image labeled "positive” only uses bright lines to represent only features that correspond to positive polarity in the original image, the image labeled "all positive" uses bright lines to represent all features of interest.
  • FIGURE 7 shows an apparatus according to the invention that illuminates the features of objects in a natural scene that correspond to the luminance features in an image of such objects, e.g., bars and edges.
  • a digitizer 30 digitizes an image of a natural scene.
  • a microprocessor or a programmed digital computer 32 obtains the locations of the bars and edges in the image and supplies this data to a light source guidance system 34.
  • the guidance system directs the light source to illuminate the locations in the natural scene corresponding to the bars and edges in the image of the scene.
  • This embodiment that can find its utility in laser shows and similar applications employs laser beams scanned over the locations of the bars and edges to illuminate these features.
  • FIGURES 8 and 9 illustrate this aspect of the invention by presenting images of different sizes and their enhanced counterparts.
  • these figures show images that differ in their respective areas by a scale factor of sixteen. An examination of these two figures clearly illustrates that application of the methods of the invention to the smaller images produces acceptable results.
  • FIGURE 10 depicts various steps according to the invention for optional enhancement of such images.
  • FIGURE 10 shows an encoder 36 at a central broadcasting station that forms an enhancement signal by supplanting an image signal with the information needed for enhancing the image, i.e., the pixels that need to be modified and the degree of modification of each pixel.
  • the broadcast of the enhancement signal is manageable because the methods of the invention modify only a small fraction of the pixels that comprise the image, thus requiring minimal expansion of the transmission bandwidth.
  • a transmitter 38 send the original image data and the enhancing information to a receiver 40 that optionally uses the information for enhancing the received image.
  • the enhancing information is transmitted to the receiver during the so-called "blank time,” in a manner similar to that utilized for producing captions for the hearing impaired, to produce an enhanced image for viewers with visual impairments.
  • FIGUREIO shows a switch 42 that controls whether the original image data or an enhanced image is sent from the receiver to a display unit 44.

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  • General Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
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Abstract

Une technique de traitement d'image produit des images modifiées au moyen de l'extraction d'importantes caractéristiques de l'image de départ, c'est-à-dire des lignes et des bords, suivie de la superposition sur l'image de départ de ces caractéristiques extraites. L'invention combine de manière prédéfinie la transformée de Hilbert des données d'image avec les données d'image pour produire la fonction dite d'énergie dont les valeurs maximales correspondent aux fortes caractéristiques de l'image. Le fait d'ajouter ces caractéristiques extraites à l'image de départ a pour résultat de produire une image améliorée. En outre, cette invention concerne des techniques permettant d'améliorer la vision du monde réel de sites naturels.
PCT/US1998/023933 1997-11-13 1998-11-10 Amelioration d'image a large bande WO1999026199A1 (fr)

Priority Applications (3)

Application Number Priority Date Filing Date Title
AU13155/99A AU1315599A (en) 1997-11-13 1998-11-10 Wide-band image enhancement
US09/234,846 US6611618B1 (en) 1997-11-13 1999-01-22 Wide-band image enhancement
US10/619,124 US7280704B2 (en) 1997-11-13 2003-07-14 Wide-band image enhancement

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US6529797P 1997-11-13 1997-11-13
US60/065,297 1997-11-13
US7012297P 1997-12-31 1997-12-31
US60/070,122 1997-12-31

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Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2000043954A2 (fr) * 1999-01-22 2000-07-27 Schepens Eye Research Institute, Inc. Amelioration d'images a large bande
WO2002089043A1 (fr) * 2001-04-30 2002-11-07 Yeda Research And Development Co., Ltd Procede et dispositif de renforcement d'image pour deficients visuels
US7280704B2 (en) 1997-11-13 2007-10-09 The Schepens Eye Research Institute, Inc. Wide-band image enhancement
US8781246B2 (en) 2009-12-24 2014-07-15 Bae Systems Plc Image enhancement
CN105651778A (zh) * 2016-01-20 2016-06-08 成都理工大学 基于共焦显微镜观测数据的矿物表面粗糙度数值计算方法
CN109398306A (zh) * 2018-09-26 2019-03-01 广州市花林景观工程有限公司 一种无人驾驶汽车

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Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6611618B1 (en) 1997-11-13 2003-08-26 Schepens Eye Research Institute, Inc. Wide-band image enhancement
US7280704B2 (en) 1997-11-13 2007-10-09 The Schepens Eye Research Institute, Inc. Wide-band image enhancement
WO2000043954A2 (fr) * 1999-01-22 2000-07-27 Schepens Eye Research Institute, Inc. Amelioration d'images a large bande
WO2000043954A3 (fr) * 1999-01-22 2000-11-09 Schepens Eye Res Inst Amelioration d'images a large bande
WO2002089043A1 (fr) * 2001-04-30 2002-11-07 Yeda Research And Development Co., Ltd Procede et dispositif de renforcement d'image pour deficients visuels
US8781246B2 (en) 2009-12-24 2014-07-15 Bae Systems Plc Image enhancement
CN105651778A (zh) * 2016-01-20 2016-06-08 成都理工大学 基于共焦显微镜观测数据的矿物表面粗糙度数值计算方法
CN105651778B (zh) * 2016-01-20 2018-11-20 成都理工大学 基于共焦显微镜观测数据的矿物表面粗糙度数值计算方法
CN109398306A (zh) * 2018-09-26 2019-03-01 广州市花林景观工程有限公司 一种无人驾驶汽车

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