WO2018166084A1 - 一种高尔夫球场图的图像处理方法、装置及设备 - Google Patents
一种高尔夫球场图的图像处理方法、装置及设备 Download PDFInfo
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- 230000003416 augmentation Effects 0.000 abstract 1
- 238000003707 image sharpening Methods 0.000 description 11
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T3/00—Geometric image transformations in the plane of the image
- G06T3/40—Scaling of whole images or parts thereof, e.g. expanding or contracting
- G06T3/4007—Scaling of whole images or parts thereof, e.g. expanding or contracting based on interpolation, e.g. bilinear interpolation
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- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
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- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30221—Sports video; Sports image
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- the present invention relates to the field of image processing technologies, and in particular, to an image processing method, apparatus and device for a golf course map.
- Satellite real-time maps or manual maps are commonly used in existing golf playing distance ranging software.
- the satellite real-life map provides an intuitive visual representation of the golf course's ranging and positioning, but due to the limited accuracy of the images provided by the satellite real-time map, it often appears in the green, bunker, middle grass, fairway and other areas of the golf course. The problem of ambiguity and low visual resolution.
- the present invention provides an image processing method, apparatus and apparatus for a golf course map in an effort to solve or at least alleviate at least one of the problems present.
- an image processing method for a golf course map comprising the steps of:
- S4 Sharpen at least one reconstructed single component image to obtain corresponding at least one sharpened single component image
- the method further includes:
- the second color golf course image is subjected to color component decomposition, and at least one single component image is retrieved, and steps S4 to S6 are repeatedly performed.
- the second color golf course image is taken as the new first color golf course image to be processed and steps S1 to S6 are re-executed.
- the decomposition method for performing color component decomposition on the first color golf ball image specifically includes: RGB decomposition, YIQ decomposition, YCbCr decomposition, HSV decomposition, CMY decomposition, or HSI decomposition.
- the reconstruction method for performing high-resolution image reconstruction on the at least one single-component image separately comprises: nearest neighbor interpolation, linear interpolation, bilinear interpolation or bicubic interpolation.
- the sharpening processing method for sharpening at least one reconstructed single-component image comprises: using a Laplacian image sharpening operator for sharpening processing, high-frequency lifting filtering, and gradient-based sharpening. Filtering, maximum-minimum sharpening transform, linear sharpening or nonlinear sharpening.
- the smoothing processing method for smoothing at least one sharpened single component image includes: neighborhood smoothing, weighted smoothing, Gaussian smoothing, median smoothing, sequential statistical smoothing, linear smoothing, or nonlinear smoothing.
- an image processing apparatus for a golf course map comprising:
- An acquisition unit configured to collect an image of a first color golf course to be processed
- a decomposition unit configured to receive the first color golf ball image of the acquisition unit and perform color component decomposition to obtain at least one single component image
- a reconstruction unit configured to receive at least one single component image of the decomposition unit, and perform high resolution image reconstruction on the at least one single component image to obtain corresponding at least one reconstructed single component image
- a sharpening processing unit configured to receive at least one reconstructed single component image of the reconstructed unit, and perform at least one reconstructed single component image to obtain a corresponding at least one sharpened single component image
- a smoothing processing unit configured to receive at least one sharpened single component image of the sharpening processing unit, and smooth at least one sharpened single channel color image to obtain corresponding at least one smoothed single component image
- a synthesizing unit configured to receive at least one smoothed single component image of the smoothing processing unit, and synthesize at least one smoothed single component image to obtain a second color golf field image.
- the device further includes a determining unit and an output unit:
- a determining unit configured to determine whether the first iteration instruction is received
- the second color golf ball image is sent to the decomposition unit, so that the decomposition unit performs color component decomposition, and at least one single component image is retrieved and sent to the sharpening processing unit.
- the determining unit is further configured to: before the first iteration instruction is received, before outputting the second color golf course image,
- the second color golf course image is transmitted to the acquisition unit if the second iteration instruction is received, such that the acquisition unit acquires the second color golf course image as the new first color golf field image to be processed.
- an image processing apparatus for a golf course map comprising:
- a memory configured to store program code
- a processor configured to execute according to instructions in program code stored in the memory:
- S4 Sharpen at least one reconstructed single component image to obtain corresponding at least one sharpened single component image
- the invention provides a processing method for a golf course map image (including but not limited to a satellite real map, an aerial photograph) based on image high resolution reconstruction and image detail enhancement. This method provides a higher resolution golf course image and a clearer visual effect.
- FIG. 1 shows a flow chart of an image processing method 100 of a golf course map in accordance with one embodiment of the present invention
- FIG. 2 shows a flow chart of an image processing method 200 of a golf course map in accordance with one embodiment of the present invention
- FIG. 3 is a block diagram showing the structure of an image processing apparatus 300 of a golf course map according to an embodiment of the present invention.
- FIG. 4 is a block diagram showing the structure of an image processing apparatus 400 of a golf course map according to another embodiment of the present invention.
- FIG. 1 shows a flow chart of an image processing method 100 in accordance with one embodiment of the present invention, including the steps of:
- the golf course image of the present embodiment includes, but is not limited to, a golf course satellite live view.
- Color component decomposition refers to decomposing a color image into a color space to describe an image color component.
- the color image decomposition method of this embodiment includes, but is not limited to, RGB decomposition, YIQ decomposition, YCbCr decomposition, HSV decomposition, CMY decomposition, or HSI decomposition.
- RGB color mode is a color standard in the industry, and RGB decomposition is through the decomposition of three color channels of red (R), green (G), and blue (B).
- RGBIQ decomposition Y is to provide brightness signals for black and white TV and color TV, that is, brightness, I for In-phase, color from orange to cyan, Q for Quadrature-phase, color from purple to yellow-green.
- YCbCr decomposition, YCBCR or Y'CBCR is a kind of color space, usually used for continuous image processing in movies, or digital photography system. In the middle, Y' is the luminance component of the color, and CB and CR are the concentration offset components of the blue and red.
- HSV decomposition H means hue H
- S means saturation
- V specifies degree
- CMY decomposition C, M, Y are Cyan, magenta or magenta (Magenta), and yellow (Yellow) shorthand, is the subtractive color mixing mode, the color produced by this method is called subtraction color.
- HIS is decomposed, and H, S, and I are shorthand for hue H (Hue), saturation S (Saturation), and luminance I (Intensity), respectively.
- the image high-resolution reconstruction technology refers to an image processing technology that recovers a high-resolution image from a low-resolution image or image sequence.
- the image reconstruction method of this embodiment includes but is not limited to nearest neighbor interpolation, linear interpolation, and double Linear interpolation or bicubic interpolation.
- the image sharpening technique refers to an image processing technique capable of reducing or eliminating low frequency components in an image without affecting high frequency components.
- the image reconstruction method of the embodiment includes, but is not limited to, a Laplacian image sharpening operator, which is high. Frequency boost filtering, gradient based sharpening filtering, maximum-minimum sharpening transform, linear or nonlinear sharpening, etc.
- Image smoothing technology refers to an image processing technology that can reduce or eliminate high frequency components in an image without affecting low frequency components.
- the smoothing method of this embodiment includes, without limitation, neighborhood smoothing, weighted smoothing, Gaussian smoothing, median smoothing, Order statistical smoothing, linear or nonlinear smoothing, etc.
- the original color golf ball image F(i, j) collected in step 101 is decomposed into three RGB three-component maps, which are respectively F R (i, j), F G (i, j), F B (i, j).
- the reconstruction method of the high-resolution image reconstruction is bicubic interpolation, step 102, through the image interpolation technique, the RGB three-component map of the low-resolution golf field satellite scene in step 101 (F R (i, j) ), F G (i, j), F B (i, j)) are interpolated as 2 times high resolution map F R2 (i, j), F G2 (i, j), F B2 (i, j) .
- Bicubic interpolation uses the gray value of 16 points around the point to be sampled for cubic interpolation, which not only considers the gray effect of four directly adjacent points, but also considers the influence of the gray value change rate between adjacent points. Provide and save more image detail information while increasing image resolution.
- A, B, and C are matrices, and their forms are as follows:
- F(i,j) represents the pixel value at the original image (i, j).
- step 103 performs image sharpening on the high-resolution interpolated image obtained in step 102 to enhance the satellite image detail, and uses a 3*3 template of Laplacian.
- the image sharpening operator l is used to sharpen the image.
- the mathematical expression is:
- 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 104 the image sharpened by the image obtained in step 103 is image smoothed, and the image details are improved, and the Gaussian image smoothing operator of the 5*5 template is used for image smoothing, and the mathematical expression is
- the smoothed image is F gau
- Gaussian smoothing is a linear smoothing filter that is used to eliminate 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 remove the ringing effect that image interpolation and sharpening may bring, and remove the noise in the image to obtain the detailed visual optimization effect of the high-resolution satellite image.
- Step 105 Combine the smoothed three RGB component maps obtained in step 104 into a color golf course satellite real map, and finally obtain a high resolution visually optimized color golf field satellite real map.
- This embodiment is applied to golf course image processing and can be used to process real-life images.
- the first color golf course image collected therein is a color satellite real image, and the purpose of this embodiment is to solve the problem that the existing golf course map does not perform image high resolution reconstruction and visual optimization.
- the golf course map high-resolution reconstruction method by image interpolation and image detail enhancement can provide a higher-resolution stadium satellite real-life map, and the image visual effect is also clearer.
- FIG. 2 shows a flow chart of an image processing method 200 in accordance with another embodiment of the present invention, including the steps of:
- the execution 208 performs color component decomposition on the second color golf course image to obtain at least one single component image, and iteratively performs steps 204-206;
- the execution 209 determines whether the second iteration instruction is received. If the second iteration instruction is received, the second color golf course image is executed as the new color processed first color golf course image. And iteratively performs steps 201 - 206.
- the bicubic interpolation operation is performed on at least one single component image to obtain at least one reconstructed single component image with twice the high resolution.
- the at least one reconstructed single-component image is subjected to image sharpening processing using a Laplacian image sharpening operator of the 3*3 template to obtain corresponding at least one sharpened single-component image.
- the at least one sharpened single component image is image smoothed by using a Gaussian image smoothing operator of the 5*5 template to obtain corresponding at least one smoothed single component image.
- the second color golf course image obtained in step 206 is determined as to whether the desired image visual effect is achieved, and if the desired effect is not obtained, the image is decomposed into an RGB three-component image ( A total of three) and proceeds to step 204. If the effect is achieved, then go to step 209 to determine the second color golf course image obtained in step 206, if necessary, to determine whether the desired image resolution is achieved, and if the desired effect is not obtained, the image is decomposed into an RGB three-component map ( A total of three) and proceeds to step 201. If an effect is achieved, a high resolution and visually optimized second color golf course image, such as a golf field map, is ultimately obtained and output.
- a high resolution and visually optimized second color golf course image such as a golf field map
- the first iteration instruction and the second iteration instruction may be selection instructions input by the user, such as pushing a to-be-selected instruction to the user after each of the second color golf course images is synthesized, and the user determines whether the second color golf course image is satisfied. Enter the selection command after the demand.
- This embodiment can be specifically applied to golf course image processing to improve satellite image or aerial photography.
- the resolution of the real map such as the map makes the pixel resolution of the real scene reach the centimeter level.
- the image visual optimization technology including image smoothing, image sharpening, and the like, is applied to a high-resolution reconstructed image (including but not limited to a golf field real image such as a satellite image and an aerial image) to improve the visual effect, thereby making the high resolution
- a high-resolution reconstructed image including but not limited to a golf field real image such as a satellite image and an aerial image
- the real-time image of the rate reconstruction is clear and the edges are obvious.
- FIG. 3 is a block diagram of an image processing apparatus 300 according to another embodiment of the present invention.
- the image processing apparatus provided in this embodiment may reside in a mobile terminal having an image processing function, such as a mobile phone or a tablet, or may reside in the mobile terminal.
- the computing device includes a collecting unit 301, configured to collect a first color golf course image to be processed;
- the decomposing unit 302 is configured to receive the first color golf ball image of the collecting unit 301 and perform color component decomposition to obtain at least one single component image;
- the reconstruction unit 303 is configured to receive the at least one single component image of the decomposition unit 302, and perform high resolution image reconstruction on the at least one single component image to obtain corresponding at least one reconstructed single component image;
- the sharpening processing unit 304 is configured to receive at least one reconstructed single component image of the reconstruction unit 303, and perform at least one reconstructed single component image to obtain a corresponding at least one sharpened single component image;
- the smoothing processing unit 305 is configured to receive at least one sharpened single component image of the sharpening processing unit, and perform smoothing processing on the at least one sharpened single component image to obtain corresponding at least one smoothed single component image;
- the synthesizing unit 306 is configured to receive at least one smoothed single component image of the smoothing processing unit 305, and synthesize at least one smoothed single component image to obtain a second color golf field image.
- the apparatus further comprises a judging unit 307 and an output unit 308:
- the determining unit 307 is configured to determine whether the first iteration instruction is received
- the output unit 308 is instructed to output the second color golf course image, or
- the second color golf ball image is sent to the decomposition unit, so that the decomposition unit performs color component decomposition, and at least one single component image is retrieved and sent to the sharpening processing unit.
- the determining unit 307 is further configured to: when the first iteration instruction is not received,
- the output unit 308 is instructed to output the second color golf course image, or
- the second color golf course image is transmitted to the acquisition unit if the second iteration instruction is received, such that the acquisition unit acquires the second color golf course image as the new first color golf field image to be processed.
- This embodiment can be used to process images that are ambiguous and have low visual resolution.
- the image high resolution reconstruction method by image interpolation and image detail enhancement in the present embodiment can provide a higher resolution image, and the image visual effect is also clearer.
- FIG. 4 shows a block diagram of an image processing apparatus 400 according to another embodiment of the present invention, including
- a memory 401 configured to store program code
- the processor 402 is configured to execute according to an instruction in the program code stored in the memory:
- S4 Sharpen at least one reconstructed single component image to obtain corresponding at least one sharpened single component image
- the processor 402 is also configured to execute:
- the second color golf course image is subjected to color component decomposition, at least one single component image is retrieved, and steps S4 to S6 are repeatedly performed.
- the method further includes:
- the second color golf course image is taken as the new first color golf course image to be processed and steps S1 to S6 are re-executed.
- the performing high-resolution image reconstruction on at least one single-component image to obtain corresponding at least one reconstructed single-component image includes:
- Sharpening at least one reconstructed single-component image to obtain corresponding at least one sharpened single-component image specifically includes: resolving at least one reconstructed single-component image using a Laplacian image of the 3*3 template The sub-image sharpening process obtains at least one sharpened single-component image.
- Smoothing at least one sharpened single-component image to obtain corresponding at least one smoothed single-component image specifically includes: smoothing at least one sharpened single-component image using a Gaussian image smoothing operator of a 5*5 template for image smoothing The process obtains at least one smoothed single component map.
- the image high resolution reconstruction method by image interpolation and image detail enhancement in the present embodiment can provide a higher resolution image, and the image visual effect is also clearer.
- modules in the devices of the embodiments can be adaptively changed and placed in one or more devices different from the embodiment.
- the modules or units or components of the embodiments may be combined into one module or unit or component, and further they may be divided into a plurality of sub-modules or sub-units or sub-components.
- any combination of the features disclosed in the specification, including the accompanying claims, the abstract and the drawings, and any methods so disclosed, or All processes or units of the device are combined.
- Each feature disclosed in this specification (including the accompanying claims, the abstract and the drawings) may be replaced by alternative features that provide the same, equivalent or similar purpose.
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Abstract
本发明公开了一种高尔夫球场图的图像处理方法,包括:S1、采集待处理的第一彩色高尔夫球场图像;S2、将上述第一彩色高尔夫球场图像进行彩色分量分解,得到至少一张单分量图;S3、分别对上述至少一张单分量图进行高分辨率图像重构得到相应的至少一张重构后的单分量图;S4、将上述至少一张重构后的单分量图进行锐化处理得到相应的至少一张锐化后的单分量图;S5、将上述至少一张锐化后的单分量图进行平滑处理得到相应的至少一张平滑后的单分量图;S6、将上述至少一张平滑后的单分量图进行合成得到第二彩色高尔夫球场图像。本发明提出的图像处理方法基于图像高分辨率重构和图像细节增强的图像的处理方法能够提供更高分辨率的图像,并且图像视觉效果也更清晰。
Description
本发明涉及图像处理技术领域,尤其是一种高尔夫球场图的图像处理方法、装置及设备。
高尔夫球场测距和定位需要利用高尔夫球场的图像来标识距离和定位。现有高尔夫打球测距软件中一般使用卫星实景图或人工示意图。卫星实景图为高尔夫球场的测距和定位提供了直观形象的画面表达,但是由于卫星实景图所提供的图像精度有限,对于球场中的果岭、沙坑、中草、球道等区域,常出现模糊不清和视觉分辨度不高的问题。
发明内容
为此,本发明提供了一种高尔夫球场图的图像处理方法、装置及设备,以力图解决或者至少缓解上面存在的至少一个问题。
根据本发明的一个方面,提供了一种高尔夫球场图的图像处理方法,包括步骤:
S1、采集待处理的第一彩色高尔夫球场图像;
S2、将第一彩色高尔夫球场图像进行彩色分量分解,得到至少一张单分量图;
S3、分别对至少一张单分量图进行高分辨率图像重构得到相应的至少一张重构后的单分量图;
S4、将至少一张重构后的单分量图进行锐化处理得到相应的至少一张锐化后的单分量图;
S5、将至少一张锐化后的单分量图进行平滑处理得到相应的至少一张平滑后的单分量图;
S6、将至少一张平滑后的单分量图进行合成得到第二彩色高尔夫球场图像。
可选地,上述将上述至少一张平滑后的单分量图进行合成得到第二彩色高尔夫球场图像后还包括:
判断是否收到第一迭代指令;
若未收到上述第一迭代指令则输出上述第二彩色高尔夫球场图像,或者,
若收到上述第一迭代指令则将上述第二彩色高尔夫球场图像进行彩色分量分解,重新得到至少一张单分量图,并重复执行步骤S4至S6。
可选地,若未收到上述第一迭代指令则:
判断是否收到第二迭代指令;
若未收到上述第二迭代指令则输出上述第二彩色高尔夫球场图像,或者
若收到上述第二迭代指令则将上述第二彩色高尔夫球场图像作为新的待处理的第一彩色高尔夫球场图像并重新执行步骤S1至S6。
可选地,将第一彩色高尔夫球场图像进行彩色分量分解的分解方法具体包括:RGB分解、YIQ分解、YCbCr分解、HSV分解、CMY分解或HSI分解。
可选地,分别对至少一张单分量图进行高分辨率图像重构的重构方法具体包括:最近邻插值、线性插值、双线性插值或双三次插值。
可选地,将至少一张重构后的单分量图进行锐化处理的锐化处理方法具体包括:采用拉普拉斯图像锐化算子进行锐化处理、高频提升滤波、基于梯度的锐化滤波、最大-最小锐化变换、线性锐化或非线性锐化。
可选地,将至少一张锐化后的单分量图进行平滑处理的平滑处理方法具体包括:邻域平滑、加权平滑、高斯平滑、中值平滑、序统计平滑、线性平滑或非线性平滑。
根据本发明的另一个方面,提供了一种高尔夫球场图的图像处理装置,包括:
采集单元,用于采集待处理的第一彩色高尔夫球场图像;
分解单元,用于接收采集单元的第一彩色高尔夫球场图像并进行彩色分量分解,得到至少一张单分量图;
重构单元,用于接收分解单元的至少一张单分量图,并分别对至少一张单分量图进行高分辨率图像重构得到相应的至少一张重构后的单分量图;
锐化处理单元,用于接收重构单元的至少一张重构后的单分量图,并将至少一张重构后的单分量图进行锐化处理得到相应的至少一张锐化后的单分量图;
平滑处理单元,用于接收锐化处理单元的至少一张锐化后的单分量图,并将至少一张锐化后的单通道色彩图进行平滑处理得到相应的至少一张平滑后的单分量图;
合成单元,用于接收平滑处理单元的至少一张平滑后的单分量图,并将至少一张平滑后的单分量图进行合成得到第二彩色高尔夫球场图像。
可选地,装置还包括判断单元和输出单元:
判断单元,用于判断是否收到第一迭代指令,
若未收到第一迭代指令则指示输出单元输出第二彩色高尔夫球场图像,或者,
若收到第一迭代指令则将第二彩色高尔夫球场图像发送至分解单元,以使分解单元进行彩色分量分解,重新得到至少一张单分量图,并发送至锐化处理单元。
可选地,判断单元还用于未收到第一迭代指令时,在输出所述第二彩色高尔夫球场图像前,
判断是否收到第二迭代指令;
若未收到第二迭代指令则指示输出单元输出第二彩色高尔夫球场图像,或者
若收到第二迭代指令则将第二彩色高尔夫球场图像发送至采集单元,以使采集单元采集第二彩色高尔夫球场图像作为新的待处理的第一彩色高尔夫球场图像。
根据本发明的又一个方面,提供了一种高尔夫球场图的图像处理设备,包括:
存储器,被配置用于存储程序代码;
处理器,被配置用于根据存储器中存储的程序代码中的指令,执行:
S1、采集待处理的第一彩色高尔夫球场图像;
S2、将第一彩色高尔夫球场图像进行彩色分量分解,得到至少一张单分量图;
S3、分别对至少一张单分量图进行高分辨率图像重构得到相应的至少一张重构后的单分量图;
S4、将至少一张重构后的单分量图进行锐化处理得到相应的至少一张锐化后的单分量图;
S5、将至少一张锐化后的单分量图进行平滑处理得到相应的至少一张平滑后的单分量图;
S6、将至少一张平滑后的单分量图进行合成得到第二彩色高尔夫球场图像。
本发明提出一种基于图像高分辨率重构和图像细节增强的高尔夫球场图图像(包括但不限于卫星实景图,航拍实景图)的处理方法。该方法能提供更高分辨率的高尔夫球场图像,并且图像视觉效果也更清晰。
为了实现上述以及相关目的,本文结合下面的描述和附图来描述某些说明性方面,这些方面指示了可以实践本文所公开的原理的各种方式,并且所有方面及其等效方面旨在落入所要求保护的主题的范围内。通过结合附图阅读下面的详细描述,本公开的上述以及其它目的、特征和优势将变得更加明显。遍及本公开,相同的附图标记通常指代相同的部件或元素。
图1示出了根据本发明一个实施例的高尔夫球场图的图像处理方法100的流程图;
图2示出了根据本发明一个实施例的高尔夫球场图的图像处理方法200的流程图;
图3示出了根据本发明一个实施例的高尔夫球场图的图像处理装置300的结构框图,以及
图4示出了根据本发明另一实施例的高尔夫球场图的图像处理设备400的结构框图。
下面将参照附图更详细地描述本公开的示例性实施例。虽然附图中显示了本公开的示例性实施例,然而应当理解,可以以各种形式实现本公开而不应被这里阐述的实施例所限制。相反,提供这些实施例是为了能够更透彻地理解本公开,并且能够将本公开的范围完整的传达给本领域的技术人员。
图1示出了根据本发明一个实施例的图像处理方法100的流程图,包括步骤:
101、采集待处理的第一彩色高尔夫球场图像;
102、将所述第一彩色高尔夫球场图像进行彩色分量分解,得到至少一张单分量图;
103、分别对所述至少一张单分量图进行高分辨率图像重构得到相应的至少一张重构后的单分量图;
104、将所述至少一张重构后的单分量图进行锐化处理得到相应的至少一张锐化后的单分量图;
105、将所述至少一张锐化后的单分量图进行平滑处理得到相应的至少一张平滑后的单分量图;
106、将所述至少一张平滑后的单分量图进行合成得到第二彩色高尔夫球场图像。
本实施例的高尔夫球场图像包括但不限于高尔夫球场卫星实景图。
彩色分量分解是指将彩色图像分解到彩色空间描述图像色彩分量,本实施例的彩色图像分解方法包括但不限于RGB分解、YIQ分解、YCbCr分解、HSV分解、CMY分解或HSI分解。
RGB色彩模式是工业界的一种颜色标准,RGB分解是通过对红(R)、绿(G)、蓝(B)三个颜色通道的分解。YIQ分解,Y是提供黑白电视及彩色电视的亮度信号,即亮度,I代表In-phase,色彩从橙色到青色,Q代表Quadrature-phase,色彩从紫色到黄绿色。YCbCr分解,YCBCR或是Y'CBCR,是色彩空间的一种,通常会用于影片中的影像连续处理,或是数字摄影***
中,Y'为颜色的亮度成分、而CB和CR则为蓝色和红色的浓度偏移量成份。HSV分解,H指色调H,S指饱和度,V指明度。CMY分解,C、M、Y分别是青(Cyan)、洋红或品红(Magenta),和黄(Yellow)的简写,是相减混色模式,用这种方法产生的颜色之所以称为相减色。HIS分解,H、S、I分别是色调H(Hue)、饱和度S(Saturation)和亮度I(Intensity)的简写。
图像高分辨率重构技术是指由一幅低分辨率图或图像序列恢复出高分辨率图的图像处理技术,本实施例的图像重构方法包括但不限于最近邻插值、线性插值、双线性插值或双三次插值等。
图像锐化技术是指能减弱或消除图像中的低频率分量但不影响高频率分量的图像处理技术,本实施例的图像重构方法包括但不限于拉普拉斯图像锐化算子、高频提升滤波、基于梯度的锐化滤波、最大-最小锐化变换、线性或非线性锐化等。
图像平滑技术是指能减弱或消除图像中的高频率分量但不影响低频率分量的图像处理技术,本实施例的平滑方法包括而不限于邻域平滑、加权平滑、高斯平滑、中值平滑、序统计平滑、线性或非线性平滑等。
彩色分量分解方法为RGB三通道分解时,步骤101中采集得到的原始彩色高尔夫球场图像F(i,j),将原图分解为RGB三分量图,共三张,分别为FR(i,j),FG(i,j),FB(i,j)。
高分辨率图像重构的重构方法为双三次插值时,步骤102,通过图像插值技术,将步骤101中的低分辨率的高尔夫球场卫星实景图的RGB三分量图(FR(i,j),FG(i,j),FB(i,j))分别插值为2倍高分辨率图FR2(i,j),FG2(i,j),FB2(i,j)。
双三次插值利用待采样点周围16个点的灰度值作三次插值,不仅考虑到4个直接相邻点的灰度影响,而且考虑到各邻点间灰度值变化率的影响,能在提高图像分辨率的同时提供和保存更多的图像细节信息。
双三次插值采用的三次多项式S(x)来逼近插值函数sin(x)/x,数学表达式为:
Fin是插值后图像,待求像素Fin(i+u,j+v)的双三次插值灰度计算式如下:
Fin(i+u,j+v)=ABC
其中,A,B,C均为矩阵,其形式如下:
A=[S(1+u) S(u) S(1-u) S(2-u)]
C=[S(1+v) S(v) S(1-v) S(2-v)]T
F(i,j)表示原图像(i,j)处的像素值。
采用拉普拉斯图像锐化算子进行锐化处理时,步骤103通过对步骤102得到的高分辨率的插值图像做图像锐化,提升卫星图像细节,采用3*3模板的拉普拉斯图像锐化算子l做图像锐化,数学表达式为:
锐化后的图像为Fl,锐化前图像为Fin
拉普拉斯算子是微分操作符,卷积运算得到的图像将使原图锐化,同时使常量区域为零。通过从插值图中减去拉普拉斯算子处理过的结果,还原常量区域,得到锐化后的图像Fl。
采用高斯平滑时,步骤104,通过对步骤103得到的图像锐化后的图像做图像平滑,提升图像细节,采用5*5模板的高斯图像平滑算子做图像平滑,数学表达式为
平滑后的图像为Fgau
高斯平滑滤波是一种线性平滑滤波,适用于消除高斯噪声,每一个像素点的值,都由其本身和邻域内的其他像素值经过加权平均后得到。通过高斯平滑滤波,可以去除图像插值和锐化可能带来的振铃效应,同时去除图像中的噪声,得到高分辨率卫星图的细节视觉优化效果。
步骤105,将步骤104得到的平滑后的三张RGB分量图合并为彩色高尔夫球场卫星实景图,最终获得高分辨率的视觉优化的彩色高尔夫球场卫星实景图。
本实施例应用在高尔夫球场图图像处理中,可以用于处理实景图像。其中采集的第一彩色高尔夫球场图像为彩色卫星实景图像,本实施例的目的是解决现有高尔夫球场图没有进行图像高分辨率重构和视觉优化的问题。本实施例通过图像插值和图像细节增强的高尔夫球场图高分辨率重构方法能提供更高分辨率的球场卫星实景图,并且图像视觉效果也更清晰。
图2示出了根据本发明另一个实施例的图像处理方法200的流程图,包括步骤:
201、采集待处理的第一彩色高尔夫球场图像;
202、将所述第一彩色高尔夫球场图像进行彩色分量分解,得到至少一张单分量图;
203、分别对所述至少一张单分量图进行高分辨率图像重构得到相应的至少一张重构后的单分量图;
204、将所述至少一张重构后的单分量图进行锐化处理得到相应的至少一张锐化后的单分量图;
205、将所述至少一张锐化后的单分量图进行平滑处理得到相应的至少一张平滑后的单分量图;
206、将所述至少一张平滑后的单分量图进行合成得到第二彩色高尔夫球场图像。
207、判断是否收到第一迭代指令;
若收到第一迭代指令则执行208将第二彩色高尔夫球场图像进行彩色分量分解,得到至少一张单分量图,并迭代执行步骤204-步骤206;
若未收到第一迭代指令则执行209判断是否收到第二迭代指令,若收到第二迭代指令刚执行步骤210将第二彩色高尔夫球场图像作为新的代处理的第一彩色高尔夫球场图像,并迭代执行步骤201-步骤206。
若未收到所述第二迭代指令则输出所述第二彩色高尔夫球场图像
优选地,分别对至少一张单分量图进行双三次插值运算得到两倍高分辨率的至少一张重构后的单分量图。
优选地,将至少一张重构后的单分量图利用3*3模板的拉普拉斯图像锐化算子做图像锐化处理得到相应的至少一张锐化后的单分量图。
优选地,将所述至少一张锐化后的单分量图利用5*5模板的高斯图像平滑算子做图像平滑处理得到相应的至少一张平滑后的单分量图。
本实施例在经过一次处理后,将步骤206得到的第二彩色高尔夫球场图像,根据需要判断是否达到了期望的图像视觉效果,若没有得到期望的效果,则将图分解为RGB三分量图(共三张)并转入步骤204。若达到效果,则转入步骤209将步骤206得到的第二彩色高尔夫球场图像,根据需要判断是否达到了期望的图像分辨率,若没有得到期望的效果,则将图分解为RGB三分量图(共三张)并转入步骤201。若达到效果,则最终获得并输出高分辨率和视觉优化的第二彩色高尔夫球场图像,如高尔夫球场实景图。
在具体实施中第一迭代指令和第二迭代指令可以为用户输入的选择指令,如在每个合成第二彩色高尔夫球场图像后向用户推送待选择指令,用户判断第二彩色高尔夫球场图像是否满足需求后输入选择指令。
本实施例可以具体应用在高尔夫球场图图像处理中以提高卫星图或航拍
图等实景图的分辨率,使实景图的像素分辨率达到厘米级。
本实施例将图像视觉优化技术,包括图像平滑、图像锐化等应用于高分辨率重构的图像(包括但不限于卫星图和航拍图等高尔夫球场实景图)的视觉效果提高,使高分辨率重构的实景图图像清晰,边缘明显。
图3示出了根据本发明另一个实施例的图像处理装置300的框图,本实施例提供的图像处理装置可以驻留在手机、平板等具有图像处理功能的移动终端中,也可以驻留在计算设备中,包括采集单元301,用于采集待处理的第一彩色高尔夫球场图像;
分解单元302,用于接收采集单元301的第一彩色高尔夫球场图像并进行彩色分量分解,得到至少一张单分量图;
重构单元303,用于接收分解单元302的所述至少一张单分量图,并分别对至少一张单分量图进行高分辨率图像重构得到相应的至少一张重构后的单分量图;
锐化处理单元304,用于接收重构单元303的至少一张重构后的单分量图,并将至少一张重构后的单分量图进行锐化处理得到相应的至少一张锐化后的单分量图;
平滑处理单元305,用于接收锐化处理单元的至少一张锐化后的单分量图,并将至少一张锐化后的单分量图进行平滑处理得到相应的至少一张平滑后的单分量图;
合成单元306,用于接收平滑处理单元305的至少一张平滑后的单分量图,并将至少一张平滑后的单分量图进行合成得到第二彩色高尔夫球场图像。
优选地,装置还包括判断单元307和输出单元308:
判断单元307,用于判断是否收到第一迭代指令,
若未收到第一迭代指令则指示输出单元308输出第二彩色高尔夫球场图像,或者,
若收到第一迭代指令则将第二彩色高尔夫球场图像发送至分解单元,以使分解单元进行彩色分量分解,重新得到至少一张单分量图,并发送至锐化处理单元。
优选地判断单元307还用于未收到第一迭代指令时,
判断是否收到第二迭代指令;
若未收到第二迭代指令则指示输出单元308输出第二彩色高尔夫球场图像,或者
若收到第二迭代指令则将第二彩色高尔夫球场图像发送至采集单元,以使采集单元采集第二彩色高尔夫球场图像作为新的待处理的第一彩色高尔夫球场图像。
本实施例可以用于处理模糊不清和视觉分辨度不高的图像。本实施例通过图像插值和图像细节增强的图像高分辨率重构方法能提供更高分辨率的图像,并且图像视觉效果也更清晰。
图4示出了根据本发明另一个实施例的图像处理设备400的框图包括,
存储器401,被配置用于存储程序代码;
处理器402,被配置用于根据存储器中存储的程序代码中的指令,执行:
S1、采集待处理的第一彩色高尔夫球场图像;
S2、将第一彩色高尔夫球场图像进行彩色分量分解,得到至少一张单分量图;
S3、分别对至少一张单分量图进行高分辨率图像重构得到相应的至少一张重构后的单分量图;
S4、将至少一张重构后的单分量图进行锐化处理得到相应的至少一张锐化后的单分量图;
S5、将至少一张锐化后的单分量图进行平滑处理得到相应的至少一张平滑后的单分量图;
S6、将至少一张平滑后的单分量图进行合成得到第二彩色高尔夫球场图像。
处理器402还用于执行:
判断是否收到第一迭代指令;
若未收到第一迭代指令则输出第二彩色高尔夫球场图像,或者,
若收到第一迭代指令则将第二彩色高尔夫球场图像进行彩色分量分解,重新得到至少一张单分量图,并重复执行步骤S4至S6。
若未收到第一迭代指令,在输出第二彩色高尔夫球场图像之前还包括:
判断是否收到第二迭代指令;
若未收到第二迭代指令则输出第二彩色高尔夫球场图像,或者
若收到第二迭代指令则将第二彩色高尔夫球场图像作为新的待处理的第一彩色高尔夫球场图像并重新执行步骤S1至S6。
其中,分别对至少一张单分量图进行高分辨率图像重构得到相应的至少一张重构后的单分量图具体包括:
分别对至少一张单分量图进行双三次插值运算得到两倍高分辨率的至少一张重构后的单分量图。
将至少一张重构后的单分量图进行锐化处理得到相应的至少一张锐化后的单分量图具体包括:将至少一张重构后的单分量图利用3*3模板的拉普拉斯图像锐化算子做图像锐化处理得到相应的至少一张锐化后的单分量图。
将至少一张锐化后的单分量图进行平滑处理得到相应的至少一张平滑后的单分量图具体包括:将至少一张锐化后的单分量图利用5*5模板的高斯图像平滑算子做图像平滑处理得到相应的至少一张平滑后的单分量图。
本实施例通过图像插值和图像细节增强的图像高分辨率重构方法能提供更高分辨率的图像,并且图像视觉效果也更清晰。
本领域那些技术人员可以理解,可以对实施例中的设备中的模块进行自适应性地改变并且把它们设置在与该实施例不同的一个或多个设备中。可以把实施例中的模块或单元或组件组合成一个模块或单元或组件,以及此外可以把它们分成多个子模块或子单元或子组件。除了这样的特征和/或过程或者单元中的至少一些是相互排斥之外,可以采用任何组合对本说明书(包括伴随的权利要求、摘要和附图)中公开的所有特征以及如此公开的任何方法或者设备的所有过程或单元进行组合。除非另外明确陈述,本说明书(包括伴随的权利要求、摘要和附图)中公开的每个特征可以由提供相同、等同或相似目的的替代特征来代替。
此外,本领域的技术人员能够理解,尽管在此所述的一些实施例包括其
它实施例中所包括的某些特征而不是其它特征,但是不同实施例的特征的组合意味着处于本发明的范围之内并且形成不同的实施例。例如,在下面的权利要求书中,所要求保护的实施例的任意之一都可以以任意的组合方式来使用。
此外,所述实施例中的一些在此被描述成可以由计算机***的处理器或者由执行所述功能的其它装置实施的方法或方法元素的组合。因此,具有用于实施所述方法或方法元素的必要指令的处理器形成用于实施该方法或方法元素的装置。此外,装置实施例的在此所述的元素是如下装置的例子:该装置用于实施由为了实施该发明的目的的元素所执行的功能。
如在此所使用的那样,除非另行规定,使用序数词“第一”、“第二”、“第三”等等来描述普通对象仅仅表示涉及类似对象的不同实例,并且并不意图暗示这样被描述的对象必须具有时间上、空间上、排序方面或者以任意其它方式的给定顺序。
尽管根据有限数量的实施例描述了本发明,但是受益于上面的描述,本技术领域内的技术人员明白,在由此描述的本发明的范围内,可以设想其它实施例。此外,应当注意,本说明书中使用的语言主要是为了可读性和教导的目的而选择的,而不是为了解释或者限定本发明的主题而选择的。因此,在不偏离所附权利要求书的范围和精神的情况下,对于本技术领域的普通技术人员来说许多修改和变更都是显而易见的。对于本发明的范围,对本发明所做的公开是说明性的,而非限制性的,本发明的范围由所附权利要求书限定。
Claims (10)
- 一种高尔夫球场图的图像处理方法,所述方法包括步骤:S1、采集待处理的第一彩色高尔夫球场图像;S2、将所述第一彩色高尔夫球场图像进行彩色分量分解,得到至少一张单分量图;S3、分别对所述至少一张单分量图进行高分辨率图像重构得到相应的至少一张重构后的单分量图;S4、将所述至少一张重构后的单分量图进行锐化处理得到相应的至少一张锐化后的单分量图;S5、将所述至少一张锐化后的单分量图进行平滑处理得到相应的至少一张平滑后的单分量图;S6、将所述至少一张平滑后的单分量图进行合成得到第二彩色高尔夫球场图像。
- 根据权利要求1所述的方法,其特征在于,将所述至少一张平滑后的单分量图进行合成得到第二彩色高尔夫球场图像后还包括:判断是否收到第一迭代指令;若未收到所述第一迭代指令则输出所述第二彩色高尔夫球场图像,或者,若收到所述第一迭代指令则将所述第二彩色高尔夫球场图像进行彩色分量分解,重新得到至少一张单分量图,并重复执行步骤S4至S6。
- 根据权利要求2所述的方法,其特征在于,若未收到所述第一迭代指令,在所述输出所述第二彩色高尔夫球场图像之前还包括:判断是否收到第二迭代指令;若未收到所述第二迭代指令则输出所述第二彩色高尔夫球场图像,或者若收到所述第二迭代指令则将所述第二彩色高尔夫球场图像作为新的待处理的第一彩色高尔夫球场图像并重新执行步骤S1至S6。
- 根据权利要求1至3任一项所述的方法,其特征在于,将所述第一彩色高尔夫球场图像进行彩色分量分解的分解方法具体包括:RGB分解、YIQ分解、YCbCr分解、HSV分解、CMY分解或HSI分解。
- 根据权利要求1至3任一项所述的方法,其特征在于,分别对所述至少一张单分量图进行高分辨率图像重构的重构方法具体包括:最近邻插值、线性插值、双线性插值或双三次插值。
- 根据权利要求1至3任一项所述的方法,其特征在于,所述将所述至少一张重构后的单分量图进行锐化处理的锐化处理方法具体包括:采用拉普拉斯图像锐化算子进行锐化、高频提升滤波、基于梯度的锐化滤波、最大-最小锐化变换、线性锐化或非线性锐化。
- 根据权利要求1至3任一项所述的方法,其特征在于,所述将所述至少一张锐化后的单分量图进行平滑处理的平滑处理方法具体包括:邻域平滑、加权平滑、高斯平滑、中值平滑、序统计平滑、线性平滑或非线性平滑。
- 一种高尔夫球场图的图像处理装置,所述装置包括:采集单元,用于采集待处理的第一彩色高尔夫球场图像;分解单元,用于接收所述采集单元的所述第一彩色高尔夫球场图像并进行彩色分量分解,得到至少一张单分量图;重构单元,用于接收所述分解单元的所述至少一张单分量图,并分别对所述至少一张单分量图进行高分辨率图像重构得到相应的至少一张重构后的单分量图;锐化处理单元,用于接收所述重构单元的所述至少一张重构后的单分量图,并将所述至少一张重构后的单分量图进行锐化处理得到相应的至少一张锐化后的单分量图;平滑处理单元,用于接收所述锐化处理单元的所述至少一张锐化后的单分量图,并将所述至少一张锐化后的单分量彩图进行平滑处理得到相应的至少一张平滑后的单分量图;合成单元,用于接收所述平滑处理单元的所述至少一张平滑后的单分量图,并将所述至少一张平滑后的单分量图进行合成得到第二彩色高尔夫球场图像。
- 根据权利要求8所述的装置,其特征在于,所述装置还包括判断单元和输出单元:所述判断单元,用于判断是否收到第一迭代指令,若未收到所述第一迭代指令则指示所述输出单元输出所述第二彩色高尔夫球场图像,或者,若收到所述第一迭代指令则将所述第二彩色高尔夫球场图像发送至所述分解单元,以使所述分解单元进行彩色分量分解,重新得到至少一张单分量图,并发送至所述锐化处理单元。
- 一种高尔夫球场图的图像处理设备,所述计算设备包括:存储器,被配置用于存储程序代码;处理器,被配置用于根据所述存储器中存储的所述程序代码中的指令,执行:S1、采集待处理的第一彩色高尔夫球场图像;S2、将所述第一彩色高尔夫球场图像进行彩色分量分解,得到至少一张单分量图;S3、分别对所述至少一张单分量图进行高分辨率图像重构得到相应的至少一张重构后的单分量图;S4、将所述至少一张重构后的单分量图进行锐化处理得到相应的至少一张锐化后的单分量图;S5、将所述至少一张锐化后的单分量图进行平滑处理得到相应的至少一张平滑后的单分量图;S6、将所述至少一张平滑后的单分量图进行合成得到第二彩色高尔夫球场图像。
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