WO2018166083A1 - Procédé d'application d'amélioration de contraste et d'optimisation de relief visuel dans une image de parcours de golf - Google Patents

Procédé d'application d'amélioration de contraste et d'optimisation de relief visuel dans une image de parcours de golf Download PDF

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Publication number
WO2018166083A1
WO2018166083A1 PCT/CN2017/088920 CN2017088920W WO2018166083A1 WO 2018166083 A1 WO2018166083 A1 WO 2018166083A1 CN 2017088920 W CN2017088920 W CN 2017088920W WO 2018166083 A1 WO2018166083 A1 WO 2018166083A1
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Prior art keywords
image
golf course
map
contrast enhancement
smoothing
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PCT/CN2017/088920
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English (en)
Chinese (zh)
Inventor
陈箫枫
潘剑佳
程健
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深圳市嘉和顺信息科技有限公司
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Publication of WO2018166083A1 publication Critical patent/WO2018166083A1/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
    • G06T5/40—Image enhancement or restoration using histogram techniques
    • 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
    • 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
    • G06T5/92—Dynamic range modification of images or parts thereof based on global image properties
    • 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
    • G06T2207/10—Image acquisition modality
    • G06T2207/10024—Color image
    • 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
    • G06T2207/10—Image acquisition modality
    • G06T2207/10032—Satellite or aerial image; Remote sensing
    • G06T2207/10041—Panchromatic image
    • 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
    • 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
    • G06T2207/20212—Image combination
    • G06T2207/20221—Image fusion; Image merging
    • 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
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30221—Sports video; Sports image
    • G06T2207/30228—Playing field

Definitions

  • the present invention relates to the use of a contrast enhancement and visual saliency optimization method in a golf course map.
  • Golf course maps are used to identify distances and locations in golf course ranging and positioning. Existing golf course maps typically use real or manual maps. Real-life maps (including but not limited to satellite and aerial maps) provide an intuitive visual representation of golf course ranging and positioning. However, the fairway, long grass, greens, bunkers and other areas in the real scene of the stadium often have problems of low contrast, inconspicuous image color, and poor visual color image.
  • the object of the present invention is to overcome the deficiencies of the prior art and to provide a contrast enhancement and visual saliency optimization method for use in a golf course, which has the characteristics of a stadium real map with higher contrast and better visual effects.
  • the present invention is achieved by an image contrast enhancement and visual saliency optimization method comprising the following steps:
  • Step 1 Obtain the original real scene map of the golf course, and the original real scene map is a color image, and the original image is decomposed into a color component map;
  • Step 2 Perform image smoothing on the original real scene of the golf course obtained in step one, and improve the details of the real scene image;
  • Step 3 Perform image sharpening on the image smoothed image obtained in step 2, and enhance the real scene image. detail;
  • Step 4 performing image contrast enhancement on the image sharpened image obtained in step 3, and improving contrast and visual saliency of the real image image;
  • Step 5 Combine the contrast-enhanced color component map obtained in step 4 into a color golf field real-life map, and determine whether the desired image visual effect is achieved according to the need, and if the desired image visual effect is achieved, the contrast enhancement is finally obtained.
  • step three a Laplacian image sharpening operator is used for image sharpening processing.
  • step two a Gaussian image smoothing operator is used for image smoothing processing.
  • step four a histogram matching technique is used to perform image contrast enhancement processing.
  • RGB component decomposition is used to decompose the color image into a color component map.
  • An application of an image contrast enhancement and visual saliency optimization method in a golf course map characterized in that the golf course includes greens, bunkers, long grasses, fairways, etc., which have low contrast and vision in existing satellite images. Poor effect, for the golf course satellite real map, the image of the golf course is image sharpening technology, image smoothing technology, image contrast enhancement technology, and the contrast and visual saliency of the image of the golf course map and part of the golf course map are improved. .
  • image sharpening techniques refer to image processing techniques that can attenuate or eliminate low frequency components in an image without affecting high frequency components, including but not limited to Laplacian image sharpening operators, High frequency boost filtering, gradient based sharpening filtering, maximum and minimum sharpening transforms, linear and nonlinear sharpening.
  • image smoothing technology refers to image processing technology that can attenuate or eliminate high frequency components in an image without affecting low frequency components, including but not limited to neighborhood smoothing, plus Weight smoothing, Gaussian smoothing, median smoothing, order statistical smoothing, linear and nonlinear smoothing.
  • image contrast enhancement technology refers to image processing technology that can increase contrast between portions of an image, including but not limited to histogram matching, histogram equalization, and image gray mapping.
  • color component decomposition refers to decomposing color images into color space to describe image color components, including without limitation RGB decomposition, YIQ decomposition, YCbCr decomposition, HSV decomposition, CMY decomposition, HSI decomposition.
  • the invention applies the image visual optimization technology, including image smoothing, image sharpening and contrast enhancement, to the image processing of the golf field satellite real image, so that the image of the real scene of the golf course is clear, the edge is obvious, the fairway, the grass in the course,
  • image visual optimization technology including image smoothing, image sharpening and contrast enhancement
  • FIG. 1 is a flowchart provided by an embodiment of the present invention.
  • an embodiment of the present invention provides an image contrast enhancement and a visual saliency optimization method at a high level.
  • the application of the satellite scene image processing in the golf course, the present invention includes two schemes, as described below.
  • Step 1 Obtain the original real scene map of the golf course, and the original real scene map is a color image, and the original image is decomposed into three RGB three-channel color maps.
  • the original golf scene real scene map is a color image F(i, j)
  • the original image is decomposed into RGB three-channel color map, a total of three, are F R (i, j), F G (i, j), F B (i, j).
  • Step 2 Perform image smoothing on the original real scene of the golf course obtained in the first step, and improve the details of the real image, (F R (i, j), F G (i, j), F B (i, j)) respectively Smoothing the image and improving the image detail.
  • F R (i, j), F G (i, j), F B (i, j) respectively Smoothing the image and improving the image detail.
  • the Gaussian image smoothing operator of the 5*5 template is used for image smoothing.
  • the mathematical expression is
  • the picture shows the original F, as the smoothed image F gau
  • Gaussian smoothing is a kind of linear smoothing filter, which is suitable for eliminating Gaussian noise.
  • the value of each pixel is obtained by weighted averaging of itself and other pixel values in the neighborhood.
  • Gaussian smoothing filtering can reduce the image. Noise, get the visual optimization effect of the details of the real scene.
  • Step 3 Perform image sharpening on the image smoothed image obtained in step 2, and improve the details of the real image.
  • the Laplacian image sharpening operator of the 3*3 template is used for image sharpening, mathematical expression Formula
  • the sharpened image is F l
  • the Laplacian operator is a differential operator, and the image obtained by the convolution operation will sharpen the original image while making the constant region zero.
  • the constant region is restored, and the sharpened image F l is obtained .
  • Step 4 Perform image contrast enhancement on the image sharpened image obtained in the third step, and improve the contrast and visual saliency of the real image image.
  • the histogram matching technique is used for image contrast enhancement.
  • the main display objects are fairways, long grasses, greens, bunkers, trees, and the like.
  • the main gray levels are concentrated in the smaller gray areas.
  • the gray level concentrated in the small gray area is mapped to [0, 255] while maintaining the relative proportion of the gray level, thereby obtaining the effect of image brightness enhancement and contrast enhancement.
  • the H -1 inverse transform function can be obtained, so that the pixel value transform function from the input graph to the desired output histogram can be obtained, and the input graph can be mapped to the desired contrast enhanced output graph. .
  • step 5 the contrast-enhanced RGB three-channel color map obtained in step four is merged into a color golf field real map, and finally a color golf field real map with contrast enhancement and visual saliency optimization is obtained.
  • step one the original real scene map of the golf course is obtained, and the original real scene map is a color image, and the original image is decomposed into an RGB three-channel color map.
  • the image of the original real scene of the golf course obtained in the first step is image smoothed, and the details of the real image are improved.
  • Step 3 Perform image sharpening on the image smoothed image obtained in step 2, and improve the details of the real image.
  • Step 4 Perform image contrast enhancement on the image sharpened image obtained in the third step, and improve the contrast and visual saliency of the real image image.
  • Step 5 Combine the contrast-enhanced RGB three-channel color map obtained in step four into a color golf field real-life map, and determine whether the desired image visual effect is achieved according to the need, and if the desired effect is not obtained, the image is decomposed into RGB three. Channel color map and go to step two. If the effect is achieved, a color golf field real map with contrast enhancement and visual saliency optimization is finally obtained.
  • the Laplacian image sharpening operator of the 3*3 template is used for image sharpening.
  • the Gaussian image smoothing operator of the 5*5 template is used for image smoothing.
  • the histogram matching technique is used for image contrast enhancement.

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

Abstract

La présente invention concerne un procédé d'amélioration de contraste d'image et d'optimisation de relief visuel ainsi que son application à un parcours de golf, le procédé comprenant les étapes consistant : à obtenir une image réaliste d'origine d'un parcours de golf, et à décomposer l'image d'origine en images en couleur à trois canaux RVB, c'est-à-dire trois images au total ; après que l'image réaliste d'origine obtenue du parcours de golf est soumise à un lissage d'image, à un renforcement de netteté et à une amélioration de contraste, à les fusionner en une image en couleur réaliste du parcours de golf ; et à déterminer, selon les exigences, si l'effet visuel souhaité pour l'image a été atteint, et si l'effet visuel souhaité pour l'image a été atteint, à obtenir finalement une image réaliste présentant un contraste amélioré et un relief visuel optimisé, et si l'effet souhaité n'est pas atteint, à décomposer l'image en images en couleur à trois canaux RVB, et à répéter le processus de traitement ci-dessus, de telle sorte que l'image de l'image réaliste du parcours de golf est claire et que les bords sont évidents. Les effets visuels, tels que les fairways, l'herbe longue, les greens, les bacs à sable et les arbres dans le parcours de golf, sont considérablement améliorés, et une image réaliste du parcours de golf, qui présente un contraste plus élevé et un meilleur effet visuel, est obtenue.
PCT/CN2017/088920 2017-03-13 2017-06-19 Procédé d'application d'amélioration de contraste et d'optimisation de relief visuel dans une image de parcours de golf WO2018166083A1 (fr)

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CN108259873B (zh) * 2018-02-01 2020-03-17 电子科技大学 一种梯度域视频对比度增强方法
CN108564072A (zh) * 2018-05-25 2018-09-21 平安科技（深圳）有限公司 基于多重处理的虹膜图像增强方法、装置、设备及介质
CN109359654B (zh) * 2018-09-18 2021-02-12 北京工商大学 基于频率调谐全局显著度和深度学习的图像分割方法及系统
CN109788197A (zh) * 2019-01-10 2019-05-21 李�杰 智能化面部识别方法及存储介质
CN110266268B (zh) * 2019-06-26 2020-11-10 武汉理工大学 一种基于图像融合识别的光伏组件故障检测方法

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