CN103163512B - Resampling method for laser radar data - Google Patents

Resampling method for laser radar data Download PDF

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CN103163512B
CN103163512B CN 201310078250 CN201310078250A CN103163512B CN 103163512 B CN103163512 B CN 103163512B CN 201310078250 CN201310078250 CN 201310078250 CN 201310078250 A CN201310078250 A CN 201310078250A CN 103163512 B CN103163512 B CN 103163512B
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distribution
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template
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王健蓉
杨春河
陈朝晖
张威泰
王立
张洪华
王振华
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北京控制工程研究所
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Abstract

本发明公开了一种激光雷达数据的重采样方法,首先计算出Y维YLen个扫描条带的零位,然后根据激光雷达三维成像敏感器扫描的X维的正弦分布特性以及视场角度范围,将X维呈正弦分布的线阵(每个条带有XNum条线阵)上XWide个像素点映射到Len个均匀分布的位置,最终将原始的XWide(宽)X(XNumXYLen)(长)的矩形点阵,规整成LenXLen的规则化模板,Len=XNumXYLen。 The present invention discloses a method of resampling data lidar, first calculates the zero dimensional YLen Y scanning strip, and then the range sine distribution characteristic X-dimensional three-dimensional imaging laser radar sensor and a scanning angle of field, the X dimension as a linear array of sinusoidal (XNum line with each strip array) of pixels is mapped to a XWide Len uniformly distributed locations, the final original XWide (width) X (XNumXYLen) (length) rectangular lattice, structured into LenXLen rules template, Len = XNumXYLen. 本发明简单有效的利用了激光雷达三维成像敏感器的扫描特性,非常适用于激光雷达数据的快速重采样。 The present invention is simple and effective use of the characteristics of the laser scanning three-dimensional imaging radar sensor is ideal for fast resampling the lidar data.

Description

一种激光雷达数据的重采样方法 A method of resampling data lidar

技术领域 FIELD

[0001] 本发明属于图像处理技术领域,涉及一种激光雷达数据的重采样方法。 [0001] The present invention belongs to the technical field of image processing, relates to a laser radar data resampling method.

背景技术 Background technique

[0002] 嫦娥三号卫星要求使用激光雷达三维成像敏感器,能在距月面loom左右的悬停阶段,对该区域进行成像,要求在短时间内选择安全着陆点,实现精避障。 [0002] Chang E 3 satellite requires three-dimensional imaging laser radar sensor can be, for imaging the region around hover phase of the lunar surface from the Loom, a short time after selection safe landing point, to achieve fine obstacle avoidance.

[0003] 激光雷达三维成像敏感器采用扫描方式获取全视场所有点的斜距和电机角的信息。 [0003] The three-dimensional imaging laser radar sensor scanning the whole field of view of access to information bit slant range and angle of the motor. 如图1所示,激光雷达三维成像敏感器采用二维扫描的方式(X维和Y维),X维、Y维的扫描波形如图2所示。 1, the three-dimensional imaging laser radar sensor scanning a two-dimensional manner (X and Y dimensions), scanning waveform X dimension, Y dimension shown in Figure 2. 每个条带X维以正弦方式扫描,Y维以步进方式与X维配合,在每一条扫描线结束时,进行一次步进,最终得到矩形点阵信息。 Each strip sinusoidally scanning X dimension, Y dimension X dimension in a stepwise manner with, at the end of each scan line, for a step, to give the final rectangular lattice information. 对获取的斜距和电机角的信息, 利用三角公式计算出激光雷达三维成像敏感器的高程坐标。 Slant range information acquired and the motor angle, elevation coordinates calculated three-dimensional imaging laser radar sensor using trigonometric formulas.

[0004] 但是该点阵信息的列方向呈条带排列,行方向呈两边密中间疏排列,对如此不规则分布的多元线阵难以应用后续的安全着陆点搜索算法。 [0004] However, the column direction of the information dot arranged in a stripe, on both sides of the middle row direction was sparse dense arrangement of polyhydric irregularly distributed linear array thus difficult to apply safe landing point of the subsequent search algorithm.

[0005] 普通的重采样方法可以减少后续数据处理的信息量,但该方法存在如下弊端:重采样时将每个数据高程变换之后按固定的距离进行选取,结果仍是不规则的图像信息,不便于后续处理。 [0005] Common resampling method can reduce the amount of subsequent data processing, but this method has the following drawbacks: the elevation data after transform for each selected fixed distance during resampling, the result is still irregular image information, not easy subsequent processing.

[0006] 因此普通的重采样方法无法规整不规则的多元线阵使其满足避障算法要求。 [0006] Thus conventional resampling method can not be structured irregular polyhydric linear algorithm to satisfy the requirements of avoidance. 为便于采样后的图像信息采用成熟的图像处理算法,有必要将其转换为规整的三维高程坐标, 从而实现数据规范化。 To facilitate the sampled image information using sophisticated image processing algorithms, it is necessary to convert it to a regular three-dimensional elevation coordinate data to achieve normalization. 鉴于嫦娥三号卫星能源、时间、存储空间的苛刻限制,需要提供激光雷达数据的快速重采样方法。 In view of the severe restrictions Chang E 3 satellite energy, time and storage space, the need to provide fast resampling method of the lidar data.

发明内容 SUMMARY

[0007] 本发明的目的是提供一种采样速度快的激光雷达数据的重采样方法,能够提供规整图像使得后续能够采用成熟的图像处理方法高效处理图像。 [0007] The object of the present invention is to provide a fast sampling lidar data resampling method can be provided such that a subsequent image can be structured using sophisticated image processing method for efficiently processing an image.

[0008] 一种激光雷达数据的重采样方法,所述激光雷达数据为激光雷达三维成像敏感器所获得的数据,所述激光雷达数据为XWideXLen维的矩形点阵所对应的斜距和电机角的信息,Len=XNumX YLen ;其中X维由XWide个点组成,Y维由YLen个扫描条带组成,每个扫描条带由XNum个线阵组成,步骤如下: [0008] The resampling method of lidar data, said data lidar three-dimensional imaging lidar sensor obtained by the laser radar data XWideXLen dimensional rectangular lattice corresponding motor angle and slant range information, Len = XNumX YLen; wherein X dimension comprises a XWide dots, Y two-dimensional scanning by the YLen strips, each strip scanned by the XNum a linear array consisting of the following steps:

[0009] 根据激光雷达三维成像敏感器扫描特性,计算每个扫描条带的零位; [0009] The three-dimensional imaging laser radar sensor scanning and calculation of zero for each scan strip;

[0010] 根据x维的视场角度范围以及偏差,计算X维的XWide个实际分布点的实际分布模型; [0010] The field angle range of the x-dimension and the deviation calculating the actual distribution the actual distribution model XWide a point X dimension;

[0011] 根据Y维的视场角度范围,计算规则化模板的等分距离; [0011] The Y dimension range of the angle of field is calculated from an aliquot of template rules;

[0012] 采用Y维的视场角度的幅值作为基准,以规则化模板的等分距离为步进,计算X维的Len个理想分布点的理想分布模型; [0012] The Y dimension of the angle of field amplitude as a reference template rule aliquots stepping distance, over the distribution model Len ideal distribution points in the X dimension is calculated;

[0013] 对于X维的每一个理想分布点,在以该理想分布点为中心,规则化模板的等分距离的一半为半径的范围内,查找该范围内X维的实际分布点的位置;求该范围内各个实际分布点的位置的均值并取整获得该理想分布点所对应的位置; [0013] For each dimension over the distribution point X, in the ideal distribution at the center point, the rule template aliquot half distance of the radius of the search for the position actual distribution within the range of the X dimension; averaging positions of the respective actual distribution within the range and rounded to obtain the position of the corresponding point over the distribution;

[0014] 根据每一个理想分布点所对应的位置以及每个扫描条带的零位建立规则化模板, 将XWideXLen维的矩形点阵规整成LenXLen维的规则化模板; [0014] The position of each point over the distribution corresponding to each scan and create rules zero article with template will XWideXLen dimensional rectangular lattice structured rules into LenXLen dimensional template;

[0015] 根据所建立的规则化模板进行重采样。 [0015] resampling according to the rules established by the template.

[0016] 所述规则化模板的建立方法如下: [0016] The method of establishing the rule template are as follows:

[0017] ScanPix[iPix] [jPix]=Xn[iPix]+ScanMid[jMid], [0017] ScanPix [iPix] [jPix] = Xn [iPix] + ScanMid [jMid],

[0018] 其中ScanPix[iPix] [jPix]为零位校正后的χ维的位置信息,iPix从1取至Len, jPix 从1 取至Len, jMid=mod(jPix, YLen), mod 为求余函数;Xn[iPix]为理想分布点iPix 所对应的位置信息,ScanMid[jMid]为jPix所对应的扫描条带jMid的零位。 [0018] wherein χ-dimensional position information after ScanPix [iPix] [jPix] zero bit correction, iPix take from 1 to Len, jPix take from 1 to Len, jMid = mod (jPix, YLen), mod is the remainder function; Xn [iPix] over the distribution position information corresponding point iPix, ScanMid [jMid] corresponding to jPix scanning strip jMid of zero.

[0019] 本发明与现有技术相比的优点在于:本发明的重采样方法通过计算得到激光雷达数据的条带零位,再根据激光雷达三维成像敏感器的扫描特性,建立基于零位对称的规则化模板,利用所述规则化模板进行重采样;从而可以有效地利用激光雷达三维成像敏感器的扫描特性,快速实现重采样,重采样后的规整图像使得后续能够采用成熟的图像处理方法高效处理图像。 [0019] The advantages of the present invention compared to the prior art in that: the resampling method of the present invention obtained by the strip lidar data calculated with zero, then the scanning characteristics of the laser radar according to three-dimensional imaging sensor is established based on the zero-bit symmetric template rule, the rule template using resampling; can be utilized effectively so that the scanning characteristics of the laser radar sensor of the three-dimensional imaging, fast implementation resampling, regular image can be re-sampled such that a subsequent use of sophisticated image processing method efficient processing of the image.

附图说明 BRIEF DESCRIPTION

[0020] 图1为激光雷达三维成像敏感器的扫描方式示意图。 [0020] FIG. 1 is a schematic view of a laser radar scanning of three-dimensional imaging sensor.

[0021] 图2为扫描波形图,图2a是16个条带的扫描波形示意图,图2b是1个条带的扫描波形示意图。 [0021] FIG. 2 is a waveform diagram of the scan, FIG. 2a is a schematic diagram of the scan waveform strip 16, FIG. 2b is a schematic diagram of a scan waveform strip.

[0022]图3为得到的基于零位对称的规则化模板的示意图。 [0022] FIG. 3 is a schematic diagram of the rule-based symmetrical zero template obtained.

[0023]图4为本发明的激光雷达数据的重采样方法流程图。 The method of resampling the lidar data [0023] FIG 4 is a flowchart of the present invention.

具体实施方式 Detailed ways

[0024] 下面结合附图和实施例对本发明作进一步的详细说明。 Drawings and embodiments of the present invention will be further described in detail [0024] below in conjunction.

[0025]本发明的激光雷达数据为激光雷达三维成像敏感器所获得的数据,所述激光雷达数据为XWideXLen维的矩形点阵所对应的斜距和电机角的信息,Len=XNumXYLen ;其中X 维由XWide个点组成,Y维由YLen个扫描条带组成,每个扫描条带由XNum个线阵组成。 [0025] Data lidar present invention is a three-dimensional imaging laser radar sensor obtained by the laser radar data information XWideXLen dimensional rectangular lattice and corresponding to the slant range of the motor angle, Len = XNumXYLen; wherein X XWide composed of two-dimensional points, Y two-dimensional scanning by the YLen strips, each strip scanned by the linear array consisting of a XNum. [0026] 如图4所示,本发明的激光雷达数据的重采样方法具体通过以下步骤实现: [0026] As shown in FIG 4, the resampling method of the present invention is a laser radar data is achieved in particular by the following steps:

[0027]步骤一:计算每个扫描条带的零位ScanMid[jMid],其中jMid从1取至YLen。 [0027] Step a: calculated for each scan stripe zero ScanMid [jMid], wherein jMid taken from 1 to YLen. 根据激光雷达三维成像敏感器扫描特性,在预估的各个条带零位附近的ScanRange范围内搜寻最小值,以此作为该条带的实际零位。 The three-dimensional imaging laser radar sensor scanning characteristics, in the individual strips with the estimated minimum value in the search range ScanRange close to zero, as the actual zero the strip. 零位为各个扫描条带对应的X维正弦扫描偏移为零的位置信息,如图2所示。 Zero-dimensional X-band sine sweep scanning conditions corresponding to the respective offset position information is zero, as shown in FIG.

[0028] 步骤二:计算X维的实际分布模型。 [0028] Step two: the actual distribution of the X dimension of the model calculation. 根据X维的视场角度范围[XLeft,XRight], 以及X维中心偏差ΧΕιτ,采用公式1建立X维的实际分布模型Xt。 The X-dimension range of the angle of field [XLeft, XRight], and the center deviation X dimension ΧΕιτ, Xt established using the actual distribution model formula 1 X dimension.

[0029] Xt=(XLeft+XRight)/2 X cos (t)+Xerr (1) [0029] Xt = (XLeft + XRight) / 2 X cos (t) + Xerr (1)

[0030] 其中,t从1取至XWide。 [0030] wherein, t take from 1 to XWide.

[0031]步骤三:计算规则化模板的等分距离Dis。 [0031] Step Three: calculation rule template aliquot distance Dis. 激光雷达的扫描特性是Y维比X维的视场角度范围窄,故最后形成的正方形规则化模板的等分距离与Y维视场角度范围[YUp, YDown]有关,参见公式2。 Characteristics of the laser radar scanning is narrower than the Y dimension X dimension of the field of view angle range, an aliquot of the regular square of the template so that the final form of the Y-dimension distance viewing angle range [YUp, YDown] For, see Equation 2.

[0032] Dis=(YUp-YDown)/2 (2) [0032] Dis = (YUp-YDown) / 2 (2)

[0033] 步骤四:计算X维的理想分布模型Xi。 [0033] Step Four: calculating ideal distribution model Xi X dimension. 采用Y维的视场角度的幅值作为基准,以规则化模板的等分距离Dis为步进,计算)(维的理想分布模型,参见公式3。 Y dimension using the magnitude of the angle of field as a reference template rule aliquots of stepping distance Dis, calculated) (over-dimensional distribution model, see Equation 3.

[0034] Xi=(YUp+YDown)/2-(il) XDis (3) [0034] Xi = (YUp + YDown) / 2- (il) XDis (3)

[0035] 其中,i从1取至Len。 [0035] where, i takes from 1 to Len.

[0036] 步骤五:遍历Len个X维的理想分布点,对于X维的每一个理想分布点i,在以该理想分布点为中心,规则化模板的等分距离的一半为半径的范围内,查找X维的实际分布点xt在该范围内的位置信息Xj,参见公式4。 [0036] Step Five: Len traversed ideal distribution point X dimension, for each distribution point I over the X dimension, over half of the distribution point to the center, the rule template aliquot is in the range from the radius , find the actual distribution of the X dimension xt within the range Xj of the position information, see equation 4.

[0037] Xj=Find (abs (Xt-Xi) < (Dis/2)) (4) [0037] Xj = Find (abs (Xt-Xi) <(Dis / 2)) (4)

[0038] 其中Xj为在该分布范围内的位置信息;Find为搜索函数。 [0038] wherein Xj is the position information within the distribution range; the Find search function.

[0039] 步骤六:遍历Len个X维的理想分布点,对于X维的每一个理想分布点iPix,求步骤五的查找范围内各个实际分布点的位置信息Xj的均值并取整,以获得该理想分布点iPix所对应的位置信息Xn[iPix],参见公式5。 [0039] Step Six: traversing Len ideal distribution point X dimension, the X dimension of each ideal distribution point iPix, averaging position information Xj respective actual distribution in the Look step five and rounding to obtain the distribution of information over the location corresponding to point iPix Xn [iPix], see equation 5.

[0040] Xn[iPix]=round(raean (Xj)) (5) [0040] Xn [iPix] = round (raean (Xj)) (5)

[0041] 其中iPix从1取至Len,round为四舍五入计算函数,mean为均值计算函数。 [0041] wherein iPix take from 1 to Len, round is a rounding function is calculated, mean is the mean value calculation function.

[0042] 步骤七:根据每一个理想分布点所对应的位置以及每个扫描条带的零位,建立基于零位对称的规则化模板ScanPix[LenXLen],参见公式6。 [0042] Step 7: According to a null position of each corresponding point distribution over each scan slice, and the establishment of rules based on a zero-bit symmetric template ScanPix [LenXLen], see equation 6.

[0043] ScanPix[iPix][jPix]=Xn[iPix]+ScanMid[jMid] (6) [0043] ScanPix [iPix] [jPix] = Xn [iPix] + ScanMid [jMid] (6)

[0044] 其中ScanPix[iPix] [jPix]为零位校正后的X维的位置信息,iPix从1取至Len, jPix 从1 取至Len,jMid=mod(jPix, YLen),mod 为求余函数;其中Xn[iPix]为步骤(6)所求的理想分布点iPix所对应的位置信息,ScanMid[jMid]为当前所属的jPix所对应的扫描条带jMid的零位。 [0044] wherein X dimension position information after ScanPix [iPix] [jPix] zero bit correction, iPix take from 1 to Len, jPix take from 1 to Len, jMid = mod (jPix, YLen), mod is the remainder function; wherein Xn [iPix] step (6) over the required location information corresponding distribution point iPix, ScanMid [jMid] with jMid jPix currently belongs to the corresponding scanning bar zero.

[0045] 所建立的基于零位对称的规则化模板,如图3。 [0045] Based on the established rules null symmetrical templates, shown in Figure 3. 经过上述步骤,将原始的XWide (宽)X (XNumXYLen)(长)的矩形点阵,规整成LenXLen的规则化模板,Len=XNumXYLen。 After the above procedure, the original XWide (width) X (XNumXYLen) (length) of the rectangular lattice, structured into LenXLen rule template, Len = XNumXYLen. 由于以Y维的维数Len为基准,Y维的位置信息是已知的,故上述规则化模板得到了X维的位置信息。 Since Len dimension Y dimension as a reference, the position information of the Y dimension is known, so the above rule templates obtained position information of the X dimension.

[0046] 步骤八:利用所述规则化模板对激光雷达数据进行重采样处理。 [0046] Step Eight: lidar data resampling using the rule templates. 提取模板相应位置的数据信息(斜距和电机角的信息),再利用三角公式计算出激光雷达三维成像敏感器的三维高程坐标,之后就可以对规整后的数据采用成熟高效的图像处理算法。 Extracting data information (slant range and the motor angle) corresponding to the position of the template, and then using trigonometric formula to calculate the three-dimensional elevation coordinate laser radar three-dimensional imaging sensor, after which the data can later structured using mature and efficient image processing algorithms.

[0047] 采用该重采样方法应用具体实例为: [0047] The resampling method using application specific examples:

[0048] 应用本发明提供的方法,嫦娥三号图像处理软件研制证明,激光三维雷达每个条带X维以正弦方式扫描,Y维(共16个条带)以步进方式与X维配合,在每一条扫描线结束时,进行一次步进,最终得到781 X 16 X 16的矩形点阵信息。 [0048] Methods provided by the invention, Chang E demonstrate the 3rd image processing software development, laser three-dimensional radar Each strip sinusoidally scanning X dimension, Y dimension (total of 16 strips) in a stepwise manner with the X dimension at the end of each scan line, for a step, to give the final rectangular lattice 781 X 16 X 16 information. 其中扫描条带数目YLen=l6,每个扫描条带的线阵数目XNum=16,X维的像素点数目XWide=781(该值为均值,实际扫描时会有1〜2个像素点的误差)。 Wherein the number of tape strips scan YLen = l6, the number of lines of each scan stripe array XNum = 16, the number of pixels in the X dimension XWide = 781 (the average value, there will be an error of 1 to 2 pixels when the actual scan points ). X维的视场角度范围[XLeft,XRight]为[-8. 52,8· 58],X维中心偏差XErr为-0· 081,Y维视场角度范围[YUp,YDown]为[-14. 81,14. 19]。 X dimension field of view angle range [XLeft, XRight] to [-8. 52,8 · 58], X is a dimensional center deviation XErr -0 · 081, Y-dimensional observation field angular range [YUp, YDown] to [-14 . 81,14. 19]. 采用本发明提供的方法和装置,首先在预估的条带零位附近的20个像素范围内(即SCanRang e=20) 计算出Y维16个扫描条带的零位,然后根据激光雷达三维成像敏感器扫描的X维的正弦分布特性以及视场角度范围,将X维呈正弦分布的线阵(每个条带有16条线阵)上781个像素点映射到256个均匀分布的位置,最终将原始的Mix (16X16)(长)的矩形点阵,规整成256X256的规则化模板。 20 pixel range within the method and apparatus of the present invention provides, in a first estimate of the strip near zero (i.e. SCanRang e = 20) Y calculated zero-dimensional scanning of the strip 16, and then the three-dimensional lidar X dimension sensitive imaging scan sinusoidal distribution characteristics and the angle of field range, the X dimension as a linear array of sinusoidal (16 lines per stripe array) of pixels 781 is mapped to positions 256 evenly distributed eventually original Mix (16X16) (length) of the rectangular lattice, structured as a template rule of 256X256.

[0049]通过所述方法后的像素点数目下降至33%,时间由普通重采样的6· 7s降至丨· 3s, 节省了81%的时间,这为之后的着陆器安全着陆点的避障搜索预留出更多的时间,因此高效的保证了嫦娥三号着陆的安全性。 [0049] The number of pixels by the method of the heads to 33% by the time of 6 · 7s common resampled reduced Shu · 3s, save 81% of the time, to avoid that the safe landing point is after the lander Search barrier set aside more time efficient and therefore ensure the safety of Chang E III landing.

[0050] 本发明说明书中未作详细描述的内容属于本领域专业技术人员的公知技术。 [0050] The content of the description of the present invention is not described in detail belonging to the known technique present the skilled in the art.

Claims (1)

  1. 1· 一种激光雷达数据的重采样方法,所述激光雷达数据为激光雷达三维成像敏感器所获得的数据,所述激光雷达数据为XWideXLen维的矩形点阵所对应的斜距和电机角的信息,Len = XNumXYLen ;其中X维由XWide个点组成,Y维由YLen个扫描条带组成,每个扫描条带由XNum个线阵组成,其特征在于,步骤如下: 根据激光雷达三维成像敏感器扫描特性,计算每个扫描条带的零位; 根据X维的视场角度范围以及偏差,计算X维的XWide个实际分布点的实际分布模型; 根据Y维的视场角度范围,计算规则化模板的等分距离; 釆用Y维的视场角度的幅值作为基准,以规则化模板的等分距离为步进,计算X维的Len个理想分布点的理想分布模型; 对于X维的每一个理想分布点,在以该理想分布点为中心,规则化模板的等分距离的一半为半径的范围内,查找该范围内X维的实际分布点的位 1. A method resampling one laser radar data, radar data is the data of the laser three-dimensional imaging laser radar sensor obtained by the laser radar data XWideXLen dimensional rectangular lattice and corresponding to the slant range of the motor angle information, Len = XNumXYLen; wherein X dimension comprises a XWide dots, Y two-dimensional scanning by the YLen strips, each strip scanned by the linear XNum a composition comprising the following steps: three-dimensional imaging lidar sensitivity scanning and calculation of each scan stripe zero; the field angle range of the X dimension and the deviation calculating the actual distribution the actual distribution model XWide two points in the X dimension; the field angle range of the dimension Y, calculation rules aliquots from the template; preclude the use of the amplitude of the angle of field Y dimension as a reference template rule aliquots stepping distance, over the distribution model Len ideal distribution point is calculated in the X dimension; for the X dimension each ideal distribution point, in the ideal distribution at the center point, the rule template aliquot half distance of the radius to search site actual distribution within the range of dimension X ;求该范围内各个实际分布点的位置的均值并取整获得该理想分布点所对应的位置; 根据每一个理想分布点所对应的位置以及每个扫描条带的零位建立规则化模板,将XWideXLen维的矩形点阵规整成LenXLen维的规则化模板; 根据所建立的规则化模板进行重采样; 所述规则化模板的建立方法如下: ScanPix[iPix][jPix] = Xn[iPix]+ScanMid[jMid], 其中ScanPix[iPix] [jPix]为零位校正后的X维的位置,iPix从1取至Len,jPix从1取至Len, jMid = mod (jPix, YLen),mod为求余函数;Xn [iPix]为理想分布点iPix所对应的位置,ScanMid[jMid]为jPix所对应的扫描条带jMid的零位。 ; Mean position of each point of the actual distribution of the required range and rounded to obtain the position of the point corresponding to the ideal distribution; zero to create a rule template in accordance with the position of each point over the distribution and corresponding to each scan strip, the XWideXLen dimensional rectangular lattice structured into LenXLen dimensional template rules; resampling template according to the rules established; method of establishing the rule template are as follows: ScanPix [iPix] [jPix] = Xn [iPix] + ScanMid [jMid], wherein the position of the X dimension ScanPix [iPix] [jPix] zero bit correction, iPix take from 1 to Len, jPix take from 1 to Len, jMid = mod (jPix, YLen), mod for the sake of It functions; Xn [iPix] distributed over the location corresponding to point iPix, ScanMid [jMid] corresponding to jPix scanning strip jMid zero position.
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