WO2002089043A1 - Procede et dispositif de renforcement d'image pour deficients visuels - Google Patents

Procede et dispositif de renforcement d'image pour deficients visuels Download PDF

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Publication number
WO2002089043A1
WO2002089043A1 PCT/US2002/013548 US0213548W WO02089043A1 WO 2002089043 A1 WO2002089043 A1 WO 2002089043A1 US 0213548 W US0213548 W US 0213548W WO 02089043 A1 WO02089043 A1 WO 02089043A1
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Prior art keywords
image
lines
relevant
characters
enhancing
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PCT/US2002/013548
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English (en)
Inventor
Shimon Ullman
Dror Zur
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Yeda Research And Development Co., Ltd
Fleit, Lois
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Application filed by Yeda Research And Development Co., Ltd, Fleit, Lois filed Critical Yeda Research And Development Co., Ltd
Priority to EP02729063A priority Critical patent/EP1386281A1/fr
Priority to IL15745902A priority patent/IL157459A0/xx
Priority to US10/473,780 priority patent/US20040136570A1/en
Publication of WO2002089043A1 publication Critical patent/WO2002089043A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/70—Denoising; Smoothing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/73—Deblurring; Sharpening
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR 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
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2200/00—Indexing scheme for image data processing or generation, in general
    • G06T2200/24—Indexing scheme for image data processing or generation, in general involving graphical user interfaces [GUIs]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20172—Image enhancement details
    • G06T2207/20192—Edge enhancement; Edge preservation

Definitions

  • the present invention relates to a-method for enhancing still and video images for the visually impaired, and more particularly, relates to an apparatus and method for testing, evaluating and reducing, the perceptual effects of people with visual disorders like Age- related Macular Degeneration (AMD).
  • AMD Age- related Macular Degeneration
  • FIG. 2 A simulated example is shown in Figure 2.
  • Picture A is the original image of Albert Einstein while Picture B is the simulation of the damage image at the retina level.
  • the simulation includes damage usually called non-geographical atrophy (the random scattered black dots) and geographical atrophy (the black spots).
  • Figure 3 shows an example of the damaged retina appears in the top view of picture A together with its visual field mapping, see bottom view of picture A.
  • the field mapping shows regions (marked by 'o') where light stimuli are perceived by the observer, and regions (marked by 'x') where light stimuli are not perceived.
  • the pictures B and C of Figure 3 shows two examples of shapes (top) and the perception, as described by the patient (bottom). As will be evident from the pictures B and C of Figure 3, the perceived shapes are distorted and blurred, but without interruption.
  • the "Ullman-Zur enhancement" algorithm that comprises, the steps of obtaining an original image, detecting and enhancing the edges and lines of the image by using Balanced Difference of Gaussians to obtain a first processed image, smoothing the original image by using a convolution of the original image with Gaussian, enhancing the contrast of the smoothed image, calculating the intensity average, AC, and the standard deviation of the intensity, SDC, of the chosen region, and stretching the intensity of the smoothed image linearly according to AC, SDC, and some specific rules to obtain a second processed enhanced image, superposing the first processed image on the second processed enhanced image to obtain the final enhanced image.
  • the "Ullman-Zur enhancement” algorithm that comprises, the steps of obtaining an original image, detecting and enhancing the edges and lines of the image by using Balanced Difference of Gaussians to obtain a first processed image, smoothing the original image by using a convolution of the original image with Gaussian, enhancing the contrast of the smoothed image, calculating the intensity average, AC,
  • the result is a final enhanced image that is more readily perceived by a visually impaired person.
  • the line and edge density is reduced (although locally it may be increased in specific regions), the prominent edges and lines have better contrast while the negligible edges and lines are smoothed out.
  • the invention makes use of the algorithms that include the change of density, regularity, and contrast, according to prominence and negligibility, of dots and textural patterns. Lines and texture may be replaced by lines or texture patterns which are denser, more regular, or have higher contrast.
  • the proposed enhancement algorithm is utilizing a normal visual effect, the filling-in [171[18][19]r20][21ir22] [23][24][25]. which extensively appears in AMD patients.
  • the filling-in enables the brain to complete missing information in specific regions, occluded regions for example, according to the context of the surroundings. In AMD patients the filling-in enables to complete the scotoma regions according to the surroundings.
  • the inventive apparatus and method enables the cortex of AMD patient to better understand the context of the surroundings and to complete the scotoma region accordingly.
  • the described method fits well general and natural images, but a specific interest is giving to images of characters (text). Characters are synthetic features and their importance comes from the significance of the reading activity for the elderly daily life.
  • the characters and words are detected by common and efficient OCR algorithm, then the characters are replaced by characters with the best font type and size, an extra apace is entered between the characters and words, the best brightness and color contrast is applied to the characters and the background, and only then the "Ullman-Zur enhancement" algorithm is applied to add an artificial enhancement, which enables better filling-in of the characters by AMD patients.
  • Later version of the algorithm will include the replacement of and change of shape, size, density and regularity of image features of various types.
  • the replacement and change may be performed according to templates of the feature. Template is an instance of a specific feature, stored and pre-tested in advance to achieve optimal perception of the feature. For example, specific objects, such as the mouth and nose of the face, may be replaced with similar templates which are best filled-in.
  • the regularity and density of features might be manipulated. Adjacent lines might be added to the edges of detected characters (in similar way to the result of applying the Ullman-Zur algorithm" on a characters image) to induce high contrast between the characters and the adjacent lines while the background has intermediate intensity.
  • the inventive apparatus and method will have real-time implementation for TV video images, camera still and video images, and computer images.
  • the invention includes evaluation methods, the size, contrast, and simulation tests, to estimate in an objective and quantitative way, the efficiency of the enhancement algorithm.
  • it includes a damage severity measurement, to measure the patient's actual damage, after the filling-in compensation, in order to estimate in advance the amount of requested enhancement.
  • the described above invention comes in addition and in combination with the common methods used for the visually impaired, which are described in the prior art section, such as magnification and contrast enhancement.
  • the invention is directed to a method for enhancing an image for a visually impaired person, comprising the steps of determining at least one discrete feature of an image, and modifying the determined feature to alter its appearance to a visually impaired person.
  • the method can further include the step of at least one of magnification of the image, contrast enhancement of the whole image, contrast enhancement of local frequency range of the image and contrast enhancement of local spatial range of the image.
  • the method include the step of at least one of adding, removing, enhancing and diminishing of the determined feature.
  • the image can be obtained from a video stream.
  • the modification can occur offline before the image is presented, or in real-time while the images are presented. In addition, the modification can be controlled in real-time by a human observer of the image.
  • the step of modifying the determined feature can include the step of changing the spatial density in the image, changing the spatial regularity of the image or changing the size and shape of the image.
  • the feature being modified can be replaced in the image with a template of the same type.
  • modifying the determined feature can include the step of changing selectively part of the feature of the image according to predefined rules.
  • the inventive method can be for enhancing an image for a visually impaired person, and can comprise the step of modifying discrete features of the image to alter their appearance to a visually impaired person.
  • the method can include the steps enhancing selectively part of the features of the image according to predefined rules, and diminishing the rest of the image.
  • the novel method can include the step of spatially smoothing the background, and contracting the background to intermediate intensities, or the background can be stretched to a bounded range of intensities.
  • the invention is essentially directed to a novel method of enhancing an image comprise the steps of determining relevant discrete lines and discrete edges in the image, and enhancing the determined lines and images.
  • the enhancement can occur by replacing each relevant line or edge by a combination of a line adjacent to an edge, by replacing each relevant line and edge by a patch of line grating, by replacing each relevant line and edge by a Gabor patch, or by replacing each relevant line and edge by two adjacent lines, one bright and one dark, and the bright line can be located at the brighter side of the background surrounding the two lines, and the dark line can be located at the darker side of the background surrounding the two lines.
  • the intensity of the lines can be stretched to extreme values.
  • the novel method for enhancement can be practiced with respect to relevant lines and texture patterns in the image.
  • the relevant lines and texture patterns in the image are enhanced by making them spatially denser, by making them more spatially regular or by stretching the intensity of the lines and texture elements to extreme values.
  • the invention has special applicability to a method for enhancing an image comprising the steps of detecting characters in an image, and enhancing the detected characters.
  • Lines and characters in the image can be enhanced by modifying their size, by modifying line attributes and fonts of the characters, by modifying the space between lines and between characters, by modifying the space between lines, between characters, and between words and/or by modifying contrast of the lines, characters and their background.
  • the method as applied to characters can include a step wherein a line grating is added adjacent to lines and to edges of the characters and/or a Gabor patch is added adjacent to lines and to edges of the characters.
  • a line grating is added adjacent to existing lines, and to edges of the characters
  • the intensity of the characters and their adjacent lines have extreme values in an opposed way
  • the background of the characters with the adjacent lines have intermediate intensity value.
  • the characters and the adjacent lines have high color contrast, and their background having intermediate color contrast.
  • One aspect of the method enables the changed features to be reduced by spatial filtering, by temporally continuous filtering, by temporal filtering and /or by spatially oriented filtering.
  • the image enhancement method of the present invention for enhancing relevant features of an image comprises the following steps: a. capturing the intensity channel of the image; b. detecting and signing the relevant features in the intensity channel of the image; c. changing discrete relevant features in the intensity channel of the image; and d. compensating the rest of the channels for the change.
  • the invention also contemplates an image enhancement method comprising the steps of: a. capturing the intensity channel of the image; b. detecting and signing the relevant features in the intensity channel of the image; c. smoothing the original image;. d. contracting or stretching the intensity channel of the smoothed image between predefined intensity limits; e. compensating the rest of the channels for the contraction or stretching; f. changing the relevant features in the intensity channel of the contrast contracted or stretched and smoothed image; and g. compensating the rest of the channels for the change; whereby relevant features of the image are enhanced and background of an image diminished.
  • the aforesaid image enhancement method can include in step f , superimposing substituting features for the relevant edges and lines on the intensity channel of the contrast contracted (or stretched) and smoothed image. Further step f can include making relevant lines and texture patterns denser and more regular in the intensity channel of the contrast contracted (or stretched) and smoothed image.
  • the present invention is directed to an image enhancement method that substitutes relevant edges and lines with two adjacent lines and diminishes the background of the image comprising the following steps:
  • a is the balance ratio and ⁇ is the space ratio;
  • c smoothing all the channels of the original image by convoluting it with an average operator, such as a gaussian smoother:
  • Im 2 G ⁇ * Im 0 . d. contracting (or stretching) the contrast of the intensity channel of the smoothed image between predefined limits, by using percentage enhancement:
  • K ⁇ and K 2 are lower and upper limits, appropriately, in the intensity channel of the smoothed image, and M ⁇ and Mi are lower and upper limits, appropriately, in the intensity channel of the contracted (stretched) image;
  • a and B are the upper and lower thresholds
  • V l (G ⁇ Q -a-G ⁇ . ⁇ o )*V 0
  • G ⁇ ( ⁇ >y) 2U ⁇ 2 a is the balance ratio and ⁇ is the space ratio;
  • Im 2 G ⁇ * Im 0 .
  • V 3 (x,y) (V 2 (x,y)-K l ) M ⁇ Ml +M
  • V 3 (x,y) M l
  • K ⁇ and K 2 are lower and upper limits, appropriately, in the intensity channel of the smoothed image, and - ⁇ i and M 2 are lower and upper limits in the intensity channel of the contracted (stretched) image;
  • V 4 (x,y) 0 else if V ⁇ (x, y) ⁇ B then
  • V 4 (x,y) 255 else
  • V4( ⁇ >y) v ( ⁇ >y)
  • a and B are the upper and lower thresholds
  • the smoothness level of the background can be controlled in offline or controlled in real-time.
  • the contraction (or stretching) level of the background can be controlled in offline or controlled in real-time.
  • the density of the enhancing lines can be controlled in offline or controlled in real-time.
  • width of enhancing lines can be controlled in offline or controlled in real-time.
  • regularity of enhanced texture is controlled in offline or controlled in real-time.
  • density of enhanced texture is controlled in offline or controlled in real-time.
  • the method can include the aspect of substituting relevant edges and lines with two adjacent lines and diminishing background of an image, in which the smoothness of the background is controlled by the width of the Gaussian ⁇ ⁇ ⁇ .
  • the substitution of the relevant edges and lines with two adjacent lines and diminishing the background can be effected by the contraction (or stretching) level of the background, controlled by the lower and upper limits values K ⁇ ⁇ K , M ⁇ , M 2 .
  • the method contemplate substituting the relevant edges and lines with two adjacent lines and diminishing the background, in which the density and the width of the enhancing lines is controlled by the parameters of the DOG, ⁇ ⁇ ' y#- ⁇ 0 5 and the thresholds values A and B, and/or substituting the relevant edges and lines with two adjacent lines and diminishing the background, in which the two-dimensional convolutions are implemented by an equivalent successive one-dimensional convolutions.
  • the method may be carried out with substituting the relevant edges and lines with two adjacent lines and diminishing the background, in which the two-dimensional convolutions are implemented by equivalent FFT transformations.
  • the invention further is directed to a character image enhancement method, comprising the following steps: a. manipulating the lines and characters in the image, and b. applying an image enhancement method according to claim 45 on the manipulated image to enhance discrete lines and characters in the image.
  • the invention as it relates to characters may proceed wherein the lines and characters in the image are manipulated by using the following steps: a. capturing the intensity channel of the image; b. detecting and signing the lines and characters in the intensity channel of the image by using an Optical Characters Recognition (OCR) or threshold algorithm; c. changing the attributes of the lines and fonts of the characters in the intensity channel of the image; d. changing the size of the lines and characters in the intensity channel of the image; e. changing the space between the lines and characters in the intensity channel of the image; f. changing the space between words in the intensity channel of the image; g. changing the color contrast between the lines and characters and their background; h. changing the brightness contrast between the lines and characters and their background; i. compensating the rest of the channels for the changes.
  • OCR Optical Characters Recognition
  • the method for enhancing characters first manipulates the lines and characters, as noted above, and then enhances the manipulated lines and characters by the steps of:
  • Vl (G ⁇ o - a - G ⁇ . ⁇ Q ) * V 0
  • a is the balance ratio and ⁇ is the space ratio
  • V 3 (x,y) M ⁇
  • ⁇ and K 2 are lower and upper limits, appropriately, in the intensity channel of the smoothed image, and j and M are lower and upper limits, appropriately, in the intensity channel of the contracted (stretched) image;
  • R3_ R2_ G 3 __ G 2 G 3 G 2 S 3 B 2 ' ' f. superimposing the two adjacent lines on the relevant edges and lines in the intensity channel of the contrast contracted (stretched) and smoothed image by using the following rule:
  • V 4 (x,y) 0 else if V ⁇ (x, y) ⁇ B then
  • V 4 (x,y) 255 else
  • V 4 ( ⁇ ,y) V 3 (x,y)
  • a and B are the upper and lower thresholds
  • the present invention includes the combination of one or more of several tests incorporated as a follow on to the enhancement method.
  • a size test can be included for determining the quality of results comprising the further steps of: a. presenting the image to a visually impaired with a size, which is below the recognition or perception threshold; b. increase the image size gradually; c. letting the visually impaired sign when he/she first identifies the object or perceive the feature in the image; and d. ranking the quality of the image according to the identification or the perception size.
  • a contrast test for determining the quality of results comprising the further steps of: a. presenting the image to the visually impaired with a contrast; which is below the recognition or perception threshold; b. increasing the image contrast gradually; c. letting the visually impaired to sign when he/she first identifies the object or perceive the feature in the image; and d. ranking the quality of the image according to the identification or the perception contrast.
  • a simulation test for determining the quality of results comprising the further steps of: a. simulating damages and perceptual effects of visually impaired individual; b. transforming an enhanced image according to the simulation; c. transforming the original images according to the simulation; d. ranking the quality according to comparison of the transformation results on the original and enhanced images.
  • the invention contemplates a Psychophysical test for the damage of the visually impaired observer that uses the following steps: a. testing the perceived uniformity of line grating with different spatial frequencies; b. testing the perceived number of missing dots in a regular array of dots with different densities; and c. testing the perceived uniformity of irregular array of dots with different irregularity levels.
  • the apparatus of the present invention includes the devices and components necessary to give effect to the algorithms disclosed as part of the invention.
  • the apparatus is provided for image enhancement for visually impaired that substitutes relevant edges and lines of an image with two adjacent lines and diminishes the background of the image by utilizing an algorithm wherein
  • G ⁇ (X, y) j s a Gaussian function with zero average and C Standard deviation
  • K i and K 2 are lower and upper limits, appropriately, in the intensity channel of the smoothed image, and Mi and M 2 are lower and upper limits, appropriately, in the intensity channel of the contracted (stretched) image;
  • a and B are the upper and lower thresholds
  • the invention provides apparatus for image enhancement for visually impaired that substitutes relevant edges and lines of an image with two adjacent lines and diminishes the background of an image by using HSV and RGB color image formats by utilizing an algorithm wherein
  • n (G ⁇ Q - ⁇ -G ⁇ . ⁇ Q )*V 0
  • Im 2 G ⁇ * Im 0 .
  • V 2 - m& ⁇ x.(R 2 ,G 2 ,B ) is contracted (or stretched) between predefined limits, by using percentage enhancement:
  • V (x,y) (V 2 (x,y) - K x ) - M M ⁇ +M ⁇
  • V 3 (x,y) M ⁇
  • R3_ _ R2_ G 3 _ G 2 G 3 G 2 B 3 B 2 > f. the two adjacent lines on relevant edges and lines in the intensity channel of the contrast contracted (stretched) and smoothed image are superimposed by using the following rule: if V ⁇ (x,y) ⁇ A then else if V ⁇ (x, y) ⁇ B then
  • V 4 (x,y) 255 else
  • V 4 ⁇ x,y V (x,y)
  • a and B are the upper and lower thresholds
  • the apparatus of the invention can be constructed and arranged that the parameters of the system filters, transformation, operators, functionality, operation, and mode of operation adjustably. Also, the adjustment of the parameters can be organized to influence the output image.
  • the apparatus can include one of the following: a. an input tuner that receives the video images in the input format and transceives them to base band; b. an Analog to Digital transceiver that samples the video frames; c. a computerized processor that modifies the sampled images; d. a digital to Analog transceiver that integrates the frames to analog video stream; e. an output mixer that transforms the base band video stream to the desired output format; and f. control panel (local or remote) enabling to control running of parameters of the method, and tests.
  • the apparatus can be housed in one of: a. a "Set top" box at the input of a TV set or a VCR (VideoCassette Recorder) - local enhancement;. b. server of a TV (Television) content provider, such as the Cables or the Satellite stations (remote enhancement); c. a Digital TV, such as High Definition TV;. d. Digital VCR player; e. DVD (Digital Versatile Disc) player; f. Close Circuit TV; g. Personal Computer (PC) card; h. Personal Computer package; i. PDA (Personal Digital Assistant). j. Handheld computer; k. Pocket PC;
  • Multimedia Player m. Computer card;. n. Internet server; o. Chip set; p. an apparatus at the input of a head mounted display.
  • the apparatus according to the invention can be used for: a. Improving the visual perception of visually impaired individual. b. Improving of Infrared images for observer with normal vision. c. Improving of Ultrasound images for observer with normal vision.
  • Figure 1 is a schematic representation showing a damaged retina of an eye with the bright spot surrounding the dark spot in the center corresponding to the damaged region; the disk shown on the right side is the blind spot of the eye.
  • Figures 2 includes a right view A and a left view B showing, respectively, an output image of Albert Einstein as perceived by a normal eye, view A, and the same image as perceived at the retinal level by an eye having a disrupting retinal scotomas, view B.
  • Figures 3 shows three pictures A, B and C each having a top view and a bottom view that are examples of a photo of a damaged retina, .top view A and the result of its visual field mapping shown below, bottom view A; a cross pattern, top view B, with its perception, bottom view B, shown below as reproduced by a patient with the damage shown in picture A; and a face drawing, top view C, with its perception, bottom view C, shown below as perceived by a patient with the damage shown in picture A.
  • Figure 4 is a flow chart showing the invention and more particularly, the "Ullman-Zur enhancement" algorithm of the present invention illustrating how an image is manipulated to obtain an enhanced image for presentation to a patient having a damaged retina.
  • Figure 5 is a flow chart showing the pre-processing required to manipulate characters before applying the "Ullman-Zur enhancement" algorithm in order to enhance the characters image for presentation to a patient having a damaged retina.
  • Figure 6 shows a series of five original images (left column) which have been enhanced, showing the algorithm results according to the teachings of the invention (middle column); in the right column the two images, the original and the enhanced images, are presented in much smaller size, a hard situation for a visually impaired person, demonstrating that the images enhanced by the practice of the present invention are clearer and more salient.
  • FIGs 7A and 7B show two optional apparatus implementations incorporating the "Ullman-Zur enhancement" algorithm.
  • an enhanced TV display is shown with the algorithm running on the set-top box (or the specific hardware) which is tuned by the Remote Control (RC). The input is either from the VCR (antenna, cables or cassette) or the CCTV camera.
  • an enhanced PC display is shown, the algorithm running on the PC, enhancing the desktop display and the display of specific applications: Word, Media Player, CCTV, etc.
  • portable computer handheld with a camera is shown, the enhanced image coming from the camera is displayed on the computer screen.
  • a head-mounted display can be connected to computer and replace the common display.
  • FIG 8 shows an example of enhanced image display and a Human Machine Interface (HMI) to control it.
  • the HMI includes control of the density of the enhanced lines, the width of. the enhanced lines, and the smoothness level of the image at the background. In addition it includes a low-vision compensation level control. This comprehensive control changes the line width, density, and the image smoothness, altogether, between two useful working situations for the AMD perception.
  • the HMI includes a contrast control and a magnification control.
  • Figure 9 shows the use of the adaptive filling-in simulation, based on receptive field expansion found by Gilbert and Wiesel [25], as a test for the ability of the enhanced images to reduce the AMD perceptual effects.
  • the processed is described by the image flow from input image through retinal level image to perceived image.
  • the adaptive filling-in transformation is described by the following formulas: m, j
  • Figure 10 shows three examples of the functional test to measure the severity of the damage of the AMD disease, after the filling-in compensation, based on the filling-in features that were found by the invention.
  • the method and apparatus of the present invention starts by obtaining an image, called the input image, and then, manipulates the image to enhance the input image in a way to enable a visually impaired person to see the image more clearly and more saliently. It changes the image features in a way that enables AMD patients to better perceive the surroundings of their scotomas in the sense that they can better fill-in the surroundings into the scotoma region.
  • the presented technique makes use of the filling-in mechanism of the AMD observer, enabling him/her to perceive the images better. For example, making the lines and edges in the image sparser and emphasizing only the relevant ones make the perception easier. On the other hand, making two dimensional texture patterns denser often enables the perception of complete pattern. In this version, the line and edge density is reduced, the prominent edges and lines have better contrast while the negligible edges and lines are smoothed out (in an improved version dots are treated in the same way).
  • Figure 4 shows the portion of the method in flow chart form showing the main flow of the unique and novel "Ullman-Zur enhancement” algorithm.
  • BDOG Balanced Difference of Gaussian
  • the original image is smoothed, and contrast enhanced.
  • the enhanced edges and lines are superimposed over the smoothed and contrast enhanced image.
  • the algorithm is preferably applied to each of the channels separately.
  • the intensity channels are defined according to the image representation, and choosing representation with unique intensity channel has special advantages.
  • an input image is obtained, usually in electronic form e.g., by deriving same from a television, computer, camera, or by scanning a visual image.
  • the image is enhanced for Age-related Macular Degeneration individuals by using the inventive method that includes the "Ullman-Zur enhancement" algorithm as follows ( Figure 4):
  • Step 10 obtaining the intensity channel (or channels) of the original image:
  • Intensity channel is expressed as an intensity value associated with each pixel of the image, such as:
  • ⁇ , y denotes a pixel in the image
  • IQ ⁇ , ) denotes an intensity
  • the intensity channel should be the actual intensity value of each pixel, usually an integer value between 0 to 255.
  • the intensity channels may be defined as each of the color channels, for example the red, green, and blue channels of the RGB representation.
  • color image is presented as HSV (Hue, Saturation, and Value for each pixel), the unique intensity channel will be the V channel, and the following algorithm will be applied with some adaptation as described later.
  • Step 10 For its unique intensity channel (or for each of its several intensity channels separately), the image obtained and processed in Step 10 undergoes the following steps:
  • Step 12 the image is subjected to edge detection and enhancement:
  • This step involves the detecting of edges and lines in the original image, and signing the locations of the detected edges and lines.
  • the sign may reflect the prominence of the edge or the line, namely it, may enhance the edge or line according to its prominence. It has been found that the detection and enhancement, performed by convoluting the image with BDOG, has special advantages.
  • ⁇ is recommended to be 1.6 but it can be any
  • the output image I ⁇ (x, y) is the BDOG image.
  • Step 14 smoothing the original image:
  • the original image is smoothed in Step 14.
  • Step 16 contracting (or stretching) the contrast of the smoothed image between predefined limits:
  • the contrast of the smoothed image is contracted (or stretched) to limit the perception of the smoothed image in Step 16.
  • the contraction (or stretching) is using part of the possible range of the intensity values, to reserve the extreme (high and low) intensities for the enhanced edges and lines (the output of the edge detection and enhancement, step 12, -t i ).
  • the following contrast contraction (or stretching) which is a modification of the percentage linear contrast enhancement, has special advantages.
  • the decision on the percentage of the intensity range of the smoothed image, which should be contracted (or stretched) is taken according to local inspection of the image, but it could be taken according to global consideration, and however, the contraction (or stretching) is done globally by the same degree for all the image locations, the procedure is:
  • I(°, y) is the column y oiI ⁇ fX, y) ,H(V) is the entropy of the column vector V :
  • I 3 (x,y) (I 2 (x,y) -(AC -k -SDQ) - 2 k ⁇ ⁇ Dc +b else if I 2 (x,y) ⁇ AC + k- SDC then
  • While ⁇ and b are upper and lower bounds, appropriately, of the new intensity range, and k is a positive number.
  • the value of ⁇ is recommended to be 150 to 200, the values of b is recommended to be 25 to 75, but they can be any number in the intensity range, keeping the order of the upper and lower bounds.
  • the value of A: is recommended to be 0.5 to 2, but it can be any positive number keeping the calculation in the intensity range.
  • AC - hSDC is nearly 0 and AC + k-SDC is nearly 255, and this "contrast enhancement" actually shrinks the contrast and the intensity range of the smoothed image.
  • Step 18 superimposing the enhanced edges and lines (step 12, /, ) on the smoothed contrast enhanced image (step 16, 3 ):
  • Step 18 the enhanced edges and lines, appearing in ] , are located and signed (superimposed) at the corresponding location in the smoothed and contrast-enhanced image, I 3 .
  • the superimposed edges and lines are prominent over their surrounding background. It is suggested to superimpose the edges and lines by using the extreme intensity values, namely, by using the maximum and minimum allowable intensity values (the brightest and the darkest values respectively). It was found that superimposing the edges and lines by using two adjacent lines, the darkest one and the brightest one, gives the best prominence, especially for the AMD patients. It was also found that the darkest line should be located at the low level side of the enhanced edge, and adjacent brightest line should be located at the high level side of the enhanced edge.
  • a and B are the upper and lower thresholds, appropriately.
  • the value of A is recommended to be in the range of 3 to 6, and the value of B is recommended to be - A, but they can be any real number with absolute value in the intensity range.
  • step 12 The process, starting at step 12 and ending at step 18, should be repeated for each of the image intensity channels, as defined in step 10.
  • Step 20 an enhanced image is obtained is Step 20, usually in digital format, which can be then displayed on a screen or monitor or printed.
  • Step 20 an enhanced image is obtained is Step 20, usually in digital format, which can be then displayed on a screen or monitor or printed.
  • the result of modifying the image by the "Ullman-Zur enhancement” algorithm as a replacement of each relevant line and edge by two adjacent lines, one is bright and one is dark, and the bright line is located at the brighter side of the background surrounding the two lines, and the dark line is located at the darker side of the background surrounding the two lines.
  • the method, and the apparatus of the present invention may use any kind of edge detector and smoothing operator, to detect edges and lines, and to smooth the image. More specifically, any combination of DOG functions might be used to enhance, detect and smooth edges, lines, or any other image feature.
  • any contrast enhancement technique may be employed as a replacement for what is described above.
  • a contrast enhancement method like linear enhancement, percentage linear enhancement, non-linear enhancement, or any other contrast enhancement, to enhance the contrast of the image.
  • one may use the described contrast enhancement method of (Step 16) with fixed values of AC and SDC for all kind of images.
  • Step 16 one may use the innovative contrast enhancement described above (Step 16) to enhance the contrast of images for any general or special purpose.
  • the values of AC and SDC might be set for each image according to the prior analysis of a specific region in the image (for example, a rectangle in the center of the image).
  • the convolution with the DOG enhances undesired features, which cannot be discarded even when optimal parameters are chosen for the DOG and the superimposing phase. Therefore, the addition of a filter before and/or after the superimposing phase is a modification that can yield good results where indicated.
  • the filtering looks for continuation of the enhanced features (the superimposed pixels) in time (for frames of video stream), and for some kind of continuation in space like the enhancement of merely oriented small line segments.
  • CT 0 for the width of the enhanced
  • the adjustment might be performed by any mean supplied with the housing apparatus.
  • ASIC Application Specific Integrated Circuit
  • the lookup table shall contain the parameters' values, and the algorithm, running on the ASIC, may use these values.
  • the values at lookup tables may be updated, manually, according to the operation of the AMD patient (adjustment operation).
  • the adjustment operation may be done directly at the apparatus, by a knob for example, or it can be done indirectly, by a wireless and remote control mean.
  • the adjustment may be performed automatically according to some predefined damage criteria and measurement of the patients.
  • the adjustment and the image modification according to the algorithm may be performed offline or in real-time. In case the adjustment and the modification are performed in real-time, they can be controlled by the observer of the image, whether it is an AMD patient or not.
  • Step 30 Obtaining the input image:
  • the image is obtained in the format and channel which best serve the successor Optical Character Recognition (OCR) algorithm
  • Step 32 Detecting characters in the image:
  • OCR algorithm is applied to detect characters in the image.
  • the OCR algorithm is chosen from existing programs or may be developed to be efficient regarding the tradeoff between adequate detection ratio and rapid performance time.
  • Step 34 a decision is made whether Text is detected, and if so, it is forwarded to Step 36.
  • Step 38 Replacing the size of the characters:
  • the characters size is replaced by the best size for AMD patients regarding normal reading distance. Right now the best size is 28.
  • Step 40 Adding space between characters and words:
  • Step 42 Enhancing the contrast of the characters image:
  • the contrast between the characters and the background is set to maximum brightness and desired colors.
  • the background at the output the "Ullman-Zur enhancement" for a black and white characters image
  • Some of the patients may choose the background to be more common with higher intensity, closer to white.
  • preprocessing is effected to detect and enhance objects of specific interest, like the icons on the Windows desktop display in order to obtain similar details.
  • the images may be enhanced by the present invention by performing the inventive method including the "Ullman-Zur enhancement" algorithm, according to the present invention, or any modification of it, on each individual image, or any second, third image, or any selected part of the input stream, and by displaying the converted images, with or without the non-converted images or any part of them, thereby making it easier for the visually impaired to see the images more clearly and to discern their content more readily.
  • the inventive method including the "Ullman-Zur enhancement" algorithm, according to the present invention, or any modification of it, on each individual image, or any second, third image, or any selected part of the input stream, and by displaying the converted images, with or without the non-converted images or any part of them, thereby making it easier for the visually impaired to see the images more clearly and to discern their content more readily.
  • real-time consideration can be embedded in the "Ullman-Zur enhancement" algorithm.
  • each of the two-dimensional convolutions may be represented by successive one-dimensional convolutions, or by FFT transformation, and in general the algorithm may be modified to yield similar results but with less processing time.
  • the example of performing the "Ullman-Zur enhancement" algorithm by using successive one-dimensional convolutions is presented below, by applying the following steps consecutively:
  • Step 50 Representing the two-dimensional DOG as two separated two-dimensional Gaussian convolutions:
  • Step 52 Replacing all the two-dimensional Gaussian convolutions with equivalent one-dimensional convolutions:
  • the two-dimensional convolution can be implemented as two successive one-dimensional convolutions:
  • Step 54 Performing only the one dimensional convolutions:
  • step 50 Whenever a two-dimensional Gaussian convolution (either the smoothing convolution or one of the DOG's convolutions, step 50) is to be performed, than the equivalent one-dimensional convolutions (step 52) are performed instead.
  • the size of the discrete 2D Gaussian matrix is (K ⁇ ⁇ ) ⁇ (K ⁇ ⁇ ) elements then the size of each of the two equivalent one-dimensional Gaussian vectors is K ⁇ ⁇ elements.
  • the saving in processing time can be presented by the operations ratio, namely the ratio between the operations needed for the two-dimensional implementation and operations needed for the one-dimensional implementation. In our case the ratio is for each performance of two-dimensional Gaussian
  • FFT(f(x, y) * g(x, y)) FFT(f(x, y)) ⁇ FFT(g(x, y))
  • the FFT operation by itself is time consuming.
  • the FFT transform requires m • n ⁇ log(w • ⁇ ) operations.
  • the number of operation is at the order of k- ⁇ -m-n. Therefore, assuming the images size do not change, for small DOG and smoothing matrices the one-dimensional convolution yields better real-time performances, and for large DOG and smoothing matrices the FFT transform can yields better real-time performances.
  • the image size is 512*512 pixels and the DOG and smoothing matrices is 7*7 pixels, the one- dimensional convolution is clearly preferred.
  • DSP's Digital Signal Processors
  • FFT transform Fast Fourier transform
  • Step 70 Present the image in HSV format:
  • V max(R,G,B)
  • S (V-min(R,G,B))/N
  • H is a function of the (R,G,B) channels.
  • Step 72 Adapted enhancement and smoothing:
  • step 12 Apply step 12 to the V channel (DOG enhancement), and step 14 (smoothing) to the original three R,G,B channels.
  • step 16 Apply step 16 to the max(R,G,B) of the smoothed image (the smoothed V channel). Change the rest of the two channels of the (R,G,B) smoothed image appropriately keeping the relation between the (R,G,B) channels of each pixel of
  • step 18 to the DOG enhanced V channel, and for each pixel of the smoothed and contrast enhanced image put it instead of (R,G,B) channel that it was originally taken from. For each pixel change the rest of the (R,G,B) channels appropriately to keep the original relation between the (R,G,B) ⁇ ⁇ before _ ⁇ -after ⁇ before ⁇ after channels ( ⁇ G r ' B b ⁇ re B after , but If the superimposed V channel was set to zero, set the other two channels also to zero).
  • the described above method and apparatus invention may include or be combined with the common methods and apparatus presently known and used for the visually impaired, which are described in the prior art section, such as magnification and contrast enhancement.
  • magnification and contrast enhancement are described in the prior art section, such as magnification and contrast enhancement.
  • the combined use of the known conventional techniques with the new proposed inventive techniques of the disclosed method can enable use of less magnification (to lose less area of the visual field) or less contrast enhancement (to leave the image more natural and vivid).
  • the variant versions of the proposed method can use some level of contrast enhancement to emphasize the enhanced features.
  • the following versions of the invention involve modifications to the unique algorithms that enable the change of density, regularity, and contrast, according to prominence and negligibility, of any feature, specifically dots and textural patterns. Textural patterns can become more regular, denser and with high contrast.
  • Later version of the algorithm will include the replacement of, and change of shape, size, density and regularity of image features according to templates of the features. Template is an instance of a specific feature, stored and pre-tested in advance to achieve optimal perception of the feature. For example, specific objects, such as the mouth and nose of the face, may be replaced with similar templates which are best filled-in.
  • Lines and edges in the image may be replaced by a patch of grating of lines (a bunch of adjacent parallel lines), a Gabor patch of lines (a grating of lines with declined intensity, mathematically represented as a grating multiplied by a centered Guassian function), or two adjacent lines one is bright and one is dark.
  • the bright line may have extreme intensity and may be located at the brighter side of the surroundings while the dark line may also have extreme intensity and may be located at the darker side of the surrounding, as the enhancing lines are usually produced by the Ullman-Zur algorithm.
  • Lines and texture may be replaced by lines or texture patterns which are denser, more regular, or have higher contrast.
  • Adjacent lines might be added to the edges of detected characters (in similar way to the result of applying the "Ullman-Zur algorithm" on a character image) to induce high contrast between the characters and the adjacent lines while the background has intermediate intensity.
  • Enhancing features such as adjacent lines, may be reduced and balanced by spatial and temporal filters to eliminate undesired effects perceived as noise or flickering.
  • the filters can be oriented in space to select specific orientation, or continuous in time to induce temporal continuity.
  • the background of the image (the image features which are not enhanced) might be differentiated from the foreground (aggregation of the image features which are enhanced) by defined rules, such as threshold mechanism. In the threshold mechanism, only image features that pass the threshold criteria will be enhanced.
  • the rest of the features (the background) can be smoothed, or their contrast might be contracted or stretched in order to become less prominent and to relatively add visual enhancement to the foreground.
  • the apparatus of the present invention is a computer programmed, or hardware designed, as described herein with reference to Figures 4 and 5, and may consist of a microprocessor, or an ASIC, with requisite I/O, storage and monitor as noted.
  • the microprocessor/ASIC is programmed/designed to perform the "Ullman-Zur enhancement" algorithm and the accompanied methods as described in the foregoing, particularly with reference to Figures 4 and 5.
  • the apparatus for performing the "Ullman-Zur enhancement" algorithm may include as a component and/or be housed, at least, in one of the following apparatus:
  • DVD Digital Versatile Disc
  • PDA Personal Digital Assistant
  • Handheld computers or Pocket PC's (Personal Computer).
  • Chip set designed for any analog and/or digital apparatus.
  • Figures 7A, 7B and 7C present examples of housing the algorithm in a TV set environment and in a personal computer environment.
  • Figure 8 presents a demonstration of enhanced image (part of video stream), and the HMI to control the enhancement adjustable parameters.
  • the quality of the enhanced image for an AMD individual may be tested, at least, by one of the following techniques:
  • the uniqueness of the simulation test is that it can be performed by a normal observer, without intervention of the subject with the specific effects, like the AMD patient in the case of AMD perception test.
  • a refinement of the present invention can include the steps of measuring the severity of the damage of the patient.
  • This severity measure may induce the amount of the enhancement needed, and may help to adjust the parameters of the "Ullman-Zur enhancement" algorithm.
  • the severity of the damage of an AMD patient may be measured, at least, by one of the following functional tests, based on the infrastructure of the filling-in effect:
  • the non-uniformity may appear, for example, as a change in the local density at the scotoma region from the average density of the surroundings) by number between 0 (non-uniform) to 5 (uniform), or by any other mean.
  • the results should better be compared with the statistical data of AMD patients, containing information about the relation between the severity of the damage and the tests results.
  • Such a database should better be created in advance, at a phase which should be called learning phase, and may precede the practical use of the tests.
  • An example for the foregoing tests is shown in Figure 10.
  • the method and apparatus of the present invention has general application for the purpose of enhancement using the "Ullman-Zur enhancement" algorithm, as described in the foregoing.
  • Examples of such purposes include:
  • Visual disorders purpose Enhancing images for any visual disorder or eye and brain diseases, in order to achieve, for example, maximum visibility while keeping the perceptual equality, or for any other purpose.
  • the present invention as specifically portrayed, can be incorporated into a more generalized system for image modification.
  • the method including the application of the enhancement algorithm and apparatus of the present invention may be incorporated as part of a more generalized system for image modification such as is described below:
  • the input of the system may be still or video images in any standard or non-standard format.
  • the output images are the converted images with the input format or in any other standard or non-standard format.
  • the method and apparatus of the inventive system for image modification can be adjusted in a variety of ways:
  • the parameters, influencing the system transformation, and influencing the output modified image can be adjusted individually, or in combination.

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Abstract

La présente invention concerne un procédé et un dispositif de renforcement d'image pour déficients visuels utilisant l'algorithme de renforcement d'Ullman-Zur. Cela implique de prendre une image originale (10), de détecter et renforcer les bords et lignes de l'image par utilisation d'une différence équilibrée des Gaussiennes (12) de façon à obtenir une première image traitée, de lisser l'image d'origine par utilisation d'une convolution de l'image d'origine avec Gaussienne (14), de renforcer le contraste de l'image lissée (16), de calculer une moyenne d'intensités (AC) ainsi qu'un écart type de l'intensité (SDC) de la région choisie, puis d'étirer linéairement l'intensité de l'image lissée en fonction de AC, SDC et quelques règles spécifiques de façon à obtenir une seconde image renforcée traitée. Enfin, on prend la première image traitée et on la superpose sur la seconde image renforcée traitée de façon à obtenir une image renforcée finale (18) qui soit plus facilement perceptible pour un déficient visuel (20).
PCT/US2002/013548 2001-04-30 2002-04-30 Procede et dispositif de renforcement d'image pour deficients visuels WO2002089043A1 (fr)

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IL15745902A IL157459A0 (en) 2001-04-30 2002-04-30 Method and apparatus for image enhancement for the visually impaired
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CN105230032A (zh) * 2013-03-15 2016-01-06 三星电子株式会社 利用自适应频率提高来创建图像中的细节
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CN114445294A (zh) * 2022-01-19 2022-05-06 北京翠鸟视觉科技有限公司 图像处理方法、计算机存储介质以及近眼显示设备

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