WO2012122788A1 - 图像校正系数的获取方法、非均匀图像校正方法及*** - Google Patents
图像校正系数的获取方法、非均匀图像校正方法及*** Download PDFInfo
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- WO2012122788A1 WO2012122788A1 PCT/CN2011/080268 CN2011080268W WO2012122788A1 WO 2012122788 A1 WO2012122788 A1 WO 2012122788A1 CN 2011080268 W CN2011080268 W CN 2011080268W WO 2012122788 A1 WO2012122788 A1 WO 2012122788A1
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- 238000000034 method Methods 0.000 title claims abstract description 70
- 238000003702 image correction Methods 0.000 title claims abstract description 69
- 238000004364 calculation method Methods 0.000 claims abstract description 26
- 230000005855 radiation Effects 0.000 claims description 19
- 230000005540 biological transmission Effects 0.000 claims 1
- 238000003331 infrared imaging Methods 0.000 description 5
- 238000003491 array Methods 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 4
- 230000000694 effects Effects 0.000 description 3
- 238000003384 imaging method Methods 0.000 description 3
- 238000013528 artificial neural network Methods 0.000 description 1
- 239000008358 core component Substances 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 239000003814 drug Substances 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 230000004297 night vision Effects 0.000 description 1
- 230000035945 sensitivity Effects 0.000 description 1
- 238000002922 simulated annealing Methods 0.000 description 1
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N25/00—Circuitry of solid-state image sensors [SSIS]; Control thereof
- H04N25/60—Noise processing, e.g. detecting, correcting, reducing or removing noise
- H04N25/67—Noise processing, e.g. detecting, correcting, reducing or removing noise applied to fixed-pattern noise, e.g. non-uniformity of response
- H04N25/671—Noise processing, e.g. detecting, correcting, reducing or removing noise applied to fixed-pattern noise, e.g. non-uniformity of response for non-uniformity detection or correction
- H04N25/672—Noise processing, e.g. detecting, correcting, reducing or removing noise applied to fixed-pattern noise, e.g. non-uniformity of response for non-uniformity detection or correction between adjacent sensors or output registers for reading a single image
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- the present invention relates to an image acquisition coefficient acquisition method, a non-uniform image correction method and system, and more particularly to an image acquisition coefficient acquisition method, a non-uniform image correction method, and a system in infrared imaging. Background technique
- infrared imaging has become an important technology of imaging systems.
- the prior art usually uses sensor arrays for infrared imaging. Therefore, the infrared focal plane sensor array imaging system is the core component of the infrared imaging system.
- infrared imaging systems are widely used in civil fields such as night vision, marine rescue, astronomy, industrial heat detection and medicine.
- infrared focal plane sensor array imaging generally has non-uniformity problems, which seriously affects image quality.
- a blank is usually used to obtain a background image under current work, so that it is necessary to temporarily intervene in the output image and interrupt the observation process.
- the flap is out of order due to movement or vibration of the machine, so that it cannot be observed.
- the use of the blank also increases power consumption, increases the size of the instrument, and brings great inconvenience to the use.
- the technical problem to be solved by the present invention is to provide an acquisition method of a non-uniform image correction coefficient, an image correction method and a system, and overcome the technical problem that the non-uniform image correction process in the prior art has high requirements on the system and the method is complicated.
- the technical solution of the present invention is: providing a method for acquiring a non-uniform image correction coefficient, the figure
- the sensor array includes a plurality of sensor units, the one sensor unit outputs a pixel value, and the sensor units in the sensor array are at least two groups, and the plurality of sensor arrays are collected under different operating temperature conditions.
- a background image the background image is grouped according to a grouping manner of the sensor units in the sensor array
- the method for acquiring the image correction coefficient includes the following steps:
- Grouping the pre-corrected images grouping pixels of the pre-corrected image output by the sensor array according to grouping of sensor units in the sensor array;
- Calculating a correction coefficient of the current background acquiring, by the group, each pixel value of the pre-corrected image, calculating an average value of the pixel values in the groups, and in the grouping of the pre-corrected image, satisfying each two sets of pixel values of the corrected image Under the condition that the sum of the squares of the differences of the average values is the smallest, the correction coefficient of the current background is calculated.
- a further technical solution of the invention is: dividing the grouping of sensor units in the sensor array into at least two groups.
- a further technical solution of the present invention is: grouping the sensor units in the sensor array into: according to the pixel value of the uniform radiation image output by the sensor unit in the sensor array, sequentially in the sensor array according to the pixel value size
- the sensor units are equally divided into groups.
- a further technical solution of the present invention is to collect a background image of the sensor array under different temperature conditions, and different temperature conditions of the plurality of uniform radiation images cover an operating temperature range of the sensor array.
- a further technical solution of the present invention is: in the grouping of the sensor units in the sensor array, the number of sensor units in the sensor array is q, the number of the packets is P, and the grouping satisfies: q/p 100.
- a further technical solution of the present invention is: in the step of calculating the image correction coefficient, calculating an average value of the pixel values in the respective groups as an average value of calculating effective pixel values in the respective groups.
- the technical solution of the present invention is: providing a non-uniform image correction method, the image is output by a sensor array, the sensor array includes a plurality of sensor units, the one sensor unit outputs a pixel value, and the sensor array is operated at different operating temperatures. a plurality of background images under conditions, wherein different temperature conditions of the plurality of background images cover an operating temperature range of the sensor array, and the background images are grouped according to a grouping manner of sensor units in the sensor array to obtain the a gain correction constant of the sensor array, the non-uniform image correction method comprising the following steps:
- Obtain the current background image Obtain the correction coefficient of the current background, and calculate the background image of the current working state of the sensor array according to the acquired background image and the correction coefficient of the current background.
- Obtain image correction result Obtain image correction result according to non-uniformity two-point correction formula.
- different temperature conditions of the plurality of background images uniformly cover an operating temperature range of the sensor array.
- the technical solution of the present invention is: constructing a non-uniform image correction system, comprising a sensor array for outputting an image and an image correction unit, the sensor array comprising a plurality of sensor units, the one sensor unit outputting a pixel value, the image
- the correction unit includes an image acquisition module that acquires an image, a background calculation module that calculates a current background image, a correction coefficient calculation module that calculates a current background image correction coefficient, a gain correction constant calculation module that calculates a gain correction constant, and an image that acquires an image correction result.
- the image acquisition module collecting a plurality of background images under different working temperature conditions output by the sensor array, wherein different temperature conditions of the plurality of background images cover an operating temperature range of the sensor array, and the background image is
- the grouping manner of the sensor units in the sensor array is grouped; the correction coefficient calculation module calculates a correction coefficient of the current background image, and the background calculation module is based on the acquired background image and the correction system of the current background image.
- the background image is calculated in the current operating state of the sensor array; said gain correction module calculates the gain correction constant sensor array normal number; the correction image acquisition module acquires an image in accordance with a result of the two-point non-uniformity correction formula.
- different temperature conditions of the plurality of background images uniformly cover an operating temperature range of the sensor array.
- the technical effects of the present invention are: providing an image correction coefficient acquisition method, a non-uniform image correction method, and a system, by using at least two groups of sensor units in the sensor array, collecting a plurality of sensor arrays under different operating temperature conditions a background image, according to the grouping of the sensor units in the sensor array, the pixels of the pre-corrected image output by the sensor array are grouped correspondingly, and each pixel value of the pre-corrected image is acquired in groups, and the groups are calculated.
- the average value of the pixel values in the group of pre-corrected images is calculated under the condition that the sum of the squares of the differences between the average values of the two sets of pixel values of the corrected image is the smallest, and the correction coefficient of the current background is calculated.
- the non-uniform image correction method by acquiring the correction coefficient of the current background, calculating the background image of the current working state of the sensor array according to the collected background image and the correction coefficient of the current background, and acquiring the image according to the non-uniformity two-point correction formula Correct the result.
- the method for acquiring an image correction coefficient, the method for correcting the image of the non-uniform image, and the system of the present invention do not require a zero pad compared to the conventional prior art. At the same time, there is no need to emphasize the use of calculating the difference between adjacent pixels, the position requirements are not high, and the calculation method is simple.
- FIG. 1 is a flow chart of obtaining a correction coefficient according to the present invention.
- FIG. 2 is a flow chart of a corrected image of the present invention.
- FIG. 3 is a schematic structural view of a calibration system of the present invention. detailed description
- a specific embodiment of the present invention is: Providing a method for acquiring an image correction coefficient, the image is output by a sensor array, the sensor array includes a plurality of sensor units, and the one sensor unit outputs one pixel. Values, the sensor units in the sensor array are at least two groups. Collecting a plurality of background images of the sensor array under different operating temperature conditions, wherein the background image refers to a uniform radiation image acquired under a certain working temperature condition, and the background image is grouped according to the sensor unit in the sensor array. Grouping. In a specific implementation process, different temperature conditions of the plurality of uniform radiation images cover an operating temperature range of the sensor array.
- the method for acquiring the image correction coefficient includes the following steps:
- Step loo group the pre-corrected images
- gp group the pixels of the pre-corrected image output by the sensor array according to the grouping of the sensor units in the sensor array.
- Step 200 Calculate a correction coefficient of the current background, gP: acquire each pixel value of the pre-corrected image by group, calculate an average value of pixel values in each group, and satisfy the corrected image in the grouping of the pre-corrected image. Under the condition that the sum of the squares of the differences between the average values of the two sets of pixel values is the smallest, the correction coefficient of the current background is calculated.
- the specific implementation process of the present invention is as follows: If the sensor array includes s sensor units, it is divided into g groups, where g takes an integer greater than 2.
- the pre-corrected images are grouped according to the grouping of the sensor units in the sensor array, gp, and the pre-corrected images are correspondingly divided into groups g, wherein g takes an integer greater than 2.
- the average value of the set of pixel values is calculated, and the image correction coefficient is calculated under the condition that the square of the difference between the average value of one set of pixel values and the average value of the other set of pixel values is the smallest.
- the pre-corrected image is divided into groups g, where g is an integer greater than 2, the average value of each group of pixel values is a Vgi , where i is an integer from 1 to g.
- offset (x, y) represents the pixel value of the pixel whose current background image coordinate is (x, y)
- K 2 , ... K n , C are correction coefficients
- ⁇ , F n (x, y) are the pixel values of the pixels whose background image coordinates are (X, y) at different operating temperatures.
- the output sensor array response value can be divided into two parts: O ⁇ offsetij+imgijXLij, where represents the output sensor array response value, offset represents the background of the sensor unit, im gij represents the image signal output by the corrected sensor unit, representing the array elements Sensitivity.
- IMG (x, y) [0 (x, y) - offset (x, y) ] XGain (x, y) (2)
- the sum of the squares of the differences between the average values of each set of pixel values of the corrected image Where, it represents the i-th group, which represents the j-th group, i ⁇ j.
- Id, K 2 , ... K n , Co are calculated according to formulas (1), (2), (3), (4), (5). In the calculation process, the minimum two are used.
- the correction coefficients ⁇ , K 2 , ... K n , C are obtained by any one of a multiplication method, a neural network method, and a simulated annealing method.
- avg ⁇ . represents the mean of the pixel values in the Z" group of F t
- avg F represents the mean of the pixel values in the group of ⁇ , where i ⁇ j.
- AF n F n (x yj X Gain (xy - F n (x 2 , y 2 ) X Gain (x 2 , y 2 ),
- K 2 , ... K n , C are obtained in the case of a plurality of sets of multiple pixels.
- the grouping of the sensor units in the sensor array is equally divided into at least two groups, and the specific grouping manner of the sensor units in the sensor array is: according to the sensors in the sensor array
- the unit outputs the pixel value size of the uniform radiation image, and sequentially divides the sensor units in the sensor array into groups according to the pixel value size.
- the non-uniformity image is caused by the difference between the pixel value of a part of the pixels and the pixel value of the other part of the pixels, if the sorting is performed according to the pixel value size of the pixels, if there is non-uniformity, the mean between the groups There must be a difference, and the non-uniformity between the groups can be minimized under the condition that the sum of the squares of the differences between the average values of the two sets of pixel values of the corrected image is minimized, and the obtained correction coefficient is more good.
- the number of sensor units in the sensor array is q
- the number of packets is P
- the grouping satisfies: q/p 100.
- a better effect is that a certain number of packets must be reached, and the number of packets is too large, and the calculation amount is large. Therefore, in the case of balancing various aspects, the grouping is satisfied: q/p 100.
- the average of the pixel values in the respective groups is calculated to calculate an average of the effective pixel values in the respective groups.
- the criterion for determining the effective pixel value is: first calculating the pixel value mean value avg of the group of pixels, and then calculating the pixel value mean square difference ⁇ of the group of pixels, and setting the pixel value of the group of pixels to gray, if
- the present invention provides a non-uniform image correction method, the image is output by a sensor array, the sensor array includes a plurality of sensor units, and the one sensor unit outputs a pixel value, and the sensor array is differently operated. a plurality of background images under temperature conditions, different temperature conditions of the plurality of background images covering an operating temperature range of the sensor array, the background images being grouped according to a grouping manner of sensor units in the sensor array, acquiring The gain correction constant of the sensor array, the non-uniform image correction method includes the following steps:
- Step 10 Obtain the current background image
- gp Obtain the correction coefficient of the current background, and calculate the background image of the current working state of the sensor array according to the acquired background image and the correction coefficient of the current background.
- the specific method of obtaining the image correction coefficient is calculated by the above image correction coefficient acquisition method, and will not be described in detail.
- F n (x, y ) is obtained by acquiring the background image, thereby obtaining the current background image minus x, y), and by calculating the offset (x, y) of each pixel of the image, the offset of all the pixels of the image can be calculated.
- F 2 , F 3 ?? F n are background images, by acquiring a background image
- SP collecting a plurality of uniform radiation images under different temperature conditions output by the sensor array, and covering different temperature conditions of the plurality of uniform radiation images The operating temperature range of the sensor array.
- the background image is F 2 , F 3 , ... F n .
- the temperature points at which the plurality of uniform radiation images are located are evenly distributed within the operating temperature range of the sensor array.
- Step 20 Acquire image correction result
- gp Obtain image correction result according to non-uniformity two-point correction formula.
- IMG (X, y) [0 (x, y) - offset (x, y) ] XGain (x, y), where offset (x, y ) indicates the background pixel value of the current coordinate (x, y), Gain (x, y) indicates the gain correction constant of the sensor unit coordinate (x, y), and IMG (X, y) indicates the coordinate after correction (x , y) pixel value, 0 (x, y) represents the pre-corrected pixel value of coordinates (x, y).
- the correction value of all the pixels in the image is obtained by the formula, that is, the corrected image is obtained.
- the acquisition of Gain (x, y) is based on the image acquisition gain correction constant of the uniform radiator under two different radiation intensities under the same ambient temperature condition.
- the image gain correction constant Gain(i, j) is:
- BlackH ( , j) BlackL(j, j) where: (i, j) represents the coordinates of the image pixel, w represents the number of lines of the image, and h represents the number of columns of the image.
- Gain(i, j) is the gain correction constant of the (i, j) sensor unit in the sensor array. By calculating the gain correction constant of each sensor unit in the sensor array, the sensor array gain is normal. number.
- the non-uniform image correction method of the invention obtains the correction coefficient of the current background, calculates the background image of the current working state of the sensor array according to the acquired background image and the correction coefficient of the current background, and acquires the image according to the non-uniformity two-point correction formula. Correct the result.
- the non-uniform image correction method of the present invention does not require a zero pad compared to the conventional prior art. At the same time, it is not necessary to emphasize the difference between the calculation of adjacent pixels, the position requirement is not high, and the calculation method is simple.
- the technical solution of the present invention is: constructing a non-uniform image correction system, comprising a sensor array 2 for outputting an image and an image correction unit 1, the sensor array 2 comprising a plurality of sensor units, the one sensor unit outputting a pixel value,
- the image correction unit 1 includes an image acquisition module 11 that acquires an image, a background calculation module 13 that calculates a current background image, a correction coefficient calculation module 12 that calculates a current background image correction coefficient, and a gain correction constant calculation module that calculates a gain correction constant.
- the image acquisition module 11 collects a sensor array a plurality of background images outputted under different operating temperature conditions of the column, different temperature conditions of the plurality of background images covering an operating temperature range of the sensor array, the background image being grouped by sensor units in the sensor array Performing grouping;
- the correction coefficient calculation module 12 calculates a correction coefficient of the current background image, and the background calculation module 13 calculates a background image in a current working state of the sensor array according to the acquired background image and the correction coefficient of the current background image;
- the gain correction constant module 14 calculates a gain correction constant of the sensor array;
- the image acquisition module 15 acquires an image correction result according to a non-uniformity two-point correction formula.
- the specific working process of the present invention is as follows: the image acquisition module 11 collects a plurality of background images under different working temperature conditions of the sensor array, and different temperature conditions of the plurality of background images cover an operating temperature range of the sensor array.
- the correction coefficient calculation module 12 acquires the correction coefficient of the current background, and the specific acquisition method is calculated by the above image correction coefficient acquisition method, and will not be described in detail herein.
- the background calculation module 13 calculates the background image of the current working state of the sensor array based on the acquired background image and the correction coefficient of the current background.
- the specific process is as follows: The current background of the coordinates (x, y) Pixel value:
- Offset (x,y) l X ⁇ l (x,y) +K 2 XF 2 (x, y) +K 3 XF 3 (x, y) + K n X
- F 2 , F 3 , ... F n are background images
- the image acquisition module 11 collects a background image
- gp collects multiple uniform radiation images under different temperature conditions output by the sensor array
- the plurality of uniform radiations Different temperature conditions of the image cover the operating temperature range of the sensor array.
- the background image is F 2 , F 3 , ... F n .
- the temperature points at which the plurality of uniform radiation images are located are evenly distributed within the operating temperature range of the sensor array.
- the image acquisition module 15 acquires an image correction result according to the non-uniformity two-point correction formula.
- the acquisition of Gain (x, y) is based on the image acquisition gain correction constant of the uniform radiator under two different radiation intensities under the same ambient temperature condition.
- the gain correction constant calculation module 14 calculates the gain correction constant of the sensor array 2, the specific process is as follows: if the images of the uniform radiators BlackH and BlackL at two different radiation intensities under the same ambient temperature condition, the image gain is normal.
- BlackH ( , j) BlackL(j, j) where: (i, j) represents the coordinates of the image pixel, w represents the number of lines of the image, and h represents the number of columns of the image.
- Gain (i, j) is the gain correction constant of the (i, j) sensor unit in the sensor array 2, and the sensor array 2 is obtained by calculating the gain correction constant of each sensor unit in the sensor array 2.
- Gain correction constant is the gain correction constant of the (i, j) sensor unit in the sensor array 2, and the sensor array 2 is obtained by calculating the gain correction constant of each sensor unit in the sensor array 2.
- the technical effect of the present invention is: providing a non-uniform image correction system, by acquiring a correction coefficient of the current background, calculating a background image of the current working state of the sensor array according to the collected background image and the correction coefficient of the current background, and then according to the non- The uniformity two-point correction formula obtains the image correction result.
- the non-uniform image correction method of the present invention does not require a zero pad compared to the conventional prior art. At the same time, there is no need to emphasize the use of calculating the difference between adjacent pixels, the position requirements are not high, and the calculation method is simple.
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Abstract
本发明涉及一种图像校正系数的获取方法、非均匀图像校正方法及***,通过采用所述传感器阵列中的传感器单元至少为两组,采集传感器阵列不同工作温度条件下的多幅背景图像,根据所述传感器阵列中的传感器单元的分组,将所述传感器阵列输出的预校正图像的像素进行相应分组,按组获取所述预校正图像的各像素值,计算所述各组中像素值的平均值,在预校正图像的分组中,满足校正后图像的每两组像素值的平均值之差的平方和最小的条件下,计算出当前背景的校正系数。本发明图像校正系数的获取方法、非均匀图像校正方法及***,与常规的现有技术相比,不需要调零挡片。同时,不需要强调采用计算相邻像素的差值,对位置要求不高,计算方法简便。
Description
图像校正系数的获取方法、 非均匀图像校正方法及*** 技术领域
本发明涉及一种图像校正系数的获取方法、 非均匀图像校正方法及***, 尤其涉及一种红外成像中图像校正系数的获取方法、 非均匀图像校正方法及系 统。 背景技术
随着红外技术的发展, 红外成像越来越成为成像***的重要技术, 现有技 术通常采用传感器阵列进行红外成像, 因此, 红外焦平面传感器阵列成像*** 是红外成像***的核心器件。 目前红外成像***广泛应用于夜视、 海上营救、 天文、 工业热探测和医学等民用领域。 然而由于制造材料、 工艺以及工作环境 等方面的原因, 红外焦平面传感器阵列成像普遍存在非均匀性问题, 严重影响 着成像质量。 现有技术对于解决非均匀图像的技术, 通常采用挡片来获得当前 工作下的背景图像, 这样就需要临时干预输出的图像, 中断观察过程。 同时, 挡片在使用过程中, 由于机器的移动或振动等导致挡片失灵, 以至于无法观察。 另外, 使用挡片还增加功耗, 增加仪器的体积, 给使用带来极大的不方便。
随着计算机技术的发展, 对于非均匀图像的校正趋向采用计算机技术进行 校正。 计算机校正技术的关键在于对校正参数的获取, 校正参数的获取主要取 决于校正系数的获取, 通过校正参数的调整达到非均匀图像的校正。 英国专利
(GB 2445254B )公开了一种非均匀图像校正方法, 其技术关键在于采用满足相 邻传感器单元输出结果差值平方和最小的条件求出校正系数, 然后通过校正系 数求出校正参数的方法。 该方法对采集的图像数量要求高, 同时, 对传感器单 元的位置要求严格, 因此, 方法实现比较复杂。 发明内容
本发明解决的技术问题是: 提供非均匀图像校正系数的获取方法、 图像校 正方法及***, 克服现有技术中非均匀图像校正过程对***要求较高、 方法实 现复杂的技术问题。
本发明的技术方案是: 提供一种非均匀图像校正系数的获取方法, 所述图
像由传感器阵列输出, 所述传感器阵列包括多个传感器单元, 所述一个传感器 单元输出一个像素值, 所述传感器阵列中的传感器单元至少为两组, 采集传感 器阵列不同工作温度条件下的多幅背景图像, 所述背景图像按所述传感器阵列 中的传感器单元的分组方式进行分组, 所述图像校正系数的获取方法包括如下 步骤:
将预校正图像分组: 根据所述传感器阵列中的传感器单元的分组, 将所述 传感器阵列输出的预校正图像的像素进行相应分组;
计算当前背景的校正系数: 按组获取所述预校正图像的各像素值, 计算所 述各组中像素值的平均值, 在预校正图像的分组中, 满足校正后图像的每两组 像素值的平均值之差的平方和最小的条件下, 计算出当前背景的校正系数。
本发明的进一步技术方案是: 将所述传感器阵列中的传感器单元的分组为 等分成至少两组。
本发明的进一步技术方案是: 所述传感器阵列中的传感器单元的分组方式 为: 根据所述传感器阵列中的传感器单元输出均匀辐射图像的像素值大小, 依 次按照像素值大小将所述传感器阵列中的传感器单元等分成多组。
本发明的进一步技术方案是:采集传感器阵列不同温度条件下的背景图像, 所述多幅均匀辐射图像的不同温度条件覆盖所述传感器阵列的工作温度范围。
本发明的进一步技术方案是: 所述传感器阵列中的传感器单元的分组中, 所述传感器阵列中的传感器单元数目为 q, 所述分组数目为 P, 分组满足: q/p 100。
本发明的进一步技术方案是: 在计算出图像校正系数步骤中, 计算所述各 组中像素值的平均值为计算所述各组中有效像素值的平均值。
本发明的技术方案是: 提供一种非均匀图像校正方法, 所述图像由传感器 阵列输出, 所述传感器阵列包括多个传感器单元, 所述一个传感器单元输出一 个像素值, 采集传感器阵列不同工作温度条件下的多幅背景图像, 所述多幅背 景图像的不同温度条件覆盖所述传感器阵列的工作温度范围, 所述背景图像按 所述传感器阵列中的传感器单元的分组方式进行分组, 获取所述传感器阵列的 增益校正常数, 所述非均匀图像校正方法包括如下步骤:
获取当前背景图像: 获取当前背景的校正系数, 根据采集的背景图像和当 前背景的校正系数计算出传感器阵列当前工作状态下的背景图像。
获取图像校正结果: 根据非均匀性两点校正公式获取图像校正结果。
本发明的进一步技术方案是: 所述多幅背景图像的不同温度条件均匀覆盖 所述传感器阵列的工作温度范围。
本发明的技术方案是: 构建一种非均匀图像校正***, 包括输出图像的传 感器阵列以及图像校正单元, 所述传感器阵列包括多个传感器单元, 所述一个 传感器单元输出一个像素值,所述图像校正单元包括采集图像的图像采集模块、 计算当前背景图像的背景计算模块、 计算当前背景图像校正系数的校正系数计 算模块、 计算增益校正常数的增益校正常数计算模块以及获取图像校正结果的 图像获取模块, 所述图像采集模块采集传感器阵列输出的不同工作温度条件下 的多幅背景图像, 所述多幅背景图像的不同温度条件覆盖所述传感器阵列的工 作温度范围, 所述背景图像按所述传感器阵列中的传感器单元的分组方式进行 分组; 所述校正系数计算模块计算当前背景图像的校正系数, 所述背景计算模 块根据采集的背景图像和当前背景图像的校正系数计算出传感器阵列当前工作 状态下的背景图像; 所述增益校正常数模块计算所述传感器阵列的增益校正常 数; 所述图像获取模块根据非均匀性两点校正公式获取图像校正结果。
本发明的进一步技术方案是: 所述多幅背景图像的不同温度条件均匀覆盖 所述传感器阵列的工作温度范围。
本发明的技术效果是: 提供一种图像校正系数的获取方法、 非均匀图像校 正方法及***, 通过采用所述传感器阵列中的传感器单元至少为两组, 采集传 感器阵列不同工作温度条件下的多幅背景图像, 根据所述传感器阵列中的传感 器单元的分组, 将所述传感器阵列输出的预校正图像的像素进行相应分组, 按 组获取所述预校正图像的各像素值, 计算所述各组中像素值的平均值, 在预校 正图像的分组中, 满足校正后图像的每两组像素值的平均值之差的平方和最小 的条件下, 计算出当前背景的校正系数。 在非均匀图像校正方法中, 通过获取 当前背景的校正系数, 根据采集的背景图像和当前背景的校正系数计算出传感 器阵列当前工作状态下的背景图像, 再根据非均匀性两点校正公式获取图像校 正结果。 本发明图像校正系数的获取方法、 非均匀图像校正方法及***与常规 的现有技术相比, 不需要调零挡片。 同时, 不需要强调采用计算相邻像素的差 值, 对位置要求不高, 计算方法简便。
附图说明
图 1为本发明校正系数获取的流程图。
图 2为本发明校正图像的流程图。
图 3为本发明校正***的结构示意图。 具体实施方式
下面结合具体实施例, 对本发明技术方案进一步说明。
如图 1所示, 本发明的具体实施方式是: 提供一种图像校正系数的获取方 法, 所述图像由传感器阵列输出, 所述传感器阵列包括多个传感器单元, 所述 一个传感器单元输出一个像素值,所述传感器阵列中的传感器单元至少为两组。 采集传感器阵列不同工作温度条件下的多幅背景图像, 所述背景图像指在某工 作温度条件下采集的一幅均匀辐射图像, 所述背景图像按所述传感器阵列中的 传感器单元的分组方式进行分组。 具体实施过程中, 所述多幅均匀辐射图像的 不同温度条件覆盖所述传感器阵列的工作温度范围。 所述图像校正系数的获取 方法包括如下步骤:
步骤 loo: 将预校正图像分组, gp : 根据所述传感器阵列中的传感器单元 的分组, 将所述传感器阵列输出的预校正图像的像素进行相应分组。
步骤 200: 计算当前背景的校正系数, gP : 按组获取所述预校正图像的各 像素值, 计算所述各组中像素值的平均值, 在预校正图像的分组中, 满足校正 后图像的每两组像素值的平均值之差的平方和最小的条件下, 计算出当前背景 的校正系数。
本发明的具体实施过程如下: 若所述传感器阵列包括 s个传感器单元, 将 其分成 g组, 其中 g取大于 2的整数。 对于预校正图像根据所述传感器阵列中 的传感器单元的分组进行相应分组, gp, 将所述预校正图像相应分成 g组, 其 中 g取大于 2的整数。 计算所述各组像素值的平均值, 在一组像素值的平均值 与另一组像素值的平均值之间的差值平方最小的条件下,计算出图像校正系数。
以下具体举例进行计算: 若将所述预校正图像相应分成 g组, 其中 g取大 于 2的整数, 其各组像素值的平均值为 aVgi, 其中 i为 1到 g中的整数。
由于: offset (x, y ) =k1 X F1 (x, y) +k2 X F2 (x, y) +--+knX Fn (x, y) +C
( 1 )
其中, offset (x, y)表示当前背景图像坐标为 (x, y) 的像素的像素值, K2、 …… Kn、 C 为校正系数, F x, y) 、 F2 (x, y)、 ···、 Fn (x, y) 为不同 工作温度下的背景图像坐标为 (X, y) 的像素的像素值。
输出的传感器阵列响应值可分成两部分: O^offsetij+imgijXLij,其中, 表示输出的传感器阵列响应值, offset表示传感器单元的背景, imgij表示校 正后传感器单元输出的图像信号, 表示阵列元素的灵敏度。
由 O^offsetij+imgijXLij变换为: imgu =(0^ - offset^)/ ,令 Gain^l/ ,得出: imgij = (Oij - off setij) XGair j,
即, IMG (x, y) =[0 (x, y) - offset (x, y) ] XGain (x, y) (2) 校正后图像的第 所有像素值的和: s画 IMG
(3) 其中, mIMG 表示校正后图像的第 Ζι组所有像素值的和,XZij表示第 组第 j个像素的 X坐标, y 表示第 组第 j个像素的 y坐标, Ci表示第∑1组 的像素个数。
校正后图像的第 平均像素值: m^IMGZ;=™mIMGZ;/d (4) 其中, 《^1^102;校正后图像的第∑1组平均像素值。
校正后图像的每两组像素值的平均值之差的平方和:
其中, 表示第 i组, 表示第 j组, i≠j。 在满足 s最小的条件下, 根 据公式 (1)、 (2)、 (3)、 (4)、 (5) 计算出 Id、 K2、 …… Kn、 Co 在计算过程中, 采用最小二乘法、 神经网络法、 模拟退火法等任一种方法求出校正系数 ^、 K2、 …… Kn、 C。
在公式 (5) 中, 令 DIMe=(m^IMG -m^IMG )2, 对 DIMe进行限定, 限定方 法如下: 求出各 、 F2、 …、 Fn 的相应组的 « -avgF f , 令 f, t=l,
…, n, avg^.表示 Ft的 Z」组中像素值的均值, avgF表 示 ^的 Ζι组中像素值的均值, 其中 i≠j。 求出 Dt的最小值 Drain和最大值 Draax, 若 DIM(;〉 Draax, 则令 DIMe=Draax; 若 DIMe<Drain, 则令 DIMe=Drain。 这样可以减小图像信息 对求解 Id、 K2、 …… Kn、 C的干扰,从而得到更佳的校正系数 Id、 K2、 …… Kn、 Co
以下以分成两个组, 每组一个像素为例, 采用最小二乘法求校正系数 、
K2、 …… Kn、 C的过程:
设一组像素的坐标为 (xl, yl),另一组像素的坐标为(x2, y2),根据公式(1)、 (2)、 (3)、 (4)、 (5), 则公式 (5)中的 S简化成以下形式:
S= [ (0 (Xl, yi) -K! X F! (Xl, yi) - K2 XF2 (Xl, …… - Kn X Fn (x Yl) _C) X
Gain(x yj- (0 (x2, y2) X Fi (x2, y2) - K2 X F2 (x2, y2) _ - KnXFn (x2,y2)_C)
XGain (x2, y2) ]2
令: Δ0= 0(χι, yi) XGain(x yj- 0(x2, y2) XGain(x2, y2),
Fi ( i, yi) X Gain (x y - Fi (x2, y2) X Gain (x2, y2),
AFn= Fn (x yj X Gain (x y - Fn (x2, y2) X Gain (x2, y2),
AC=C X (Gain (x yj - Gain (x2, y2) )
贝 ij: S= (AO-KiXAFi- K2XAF2-…… - KnXAFn-AC) 2 (6)
先分别对公式 (6) 中的 Id、 K2、 …… Κη、 C求偏导数, 并令偏导数为零, 得到以下方程组:
△0XAF厂 Ki X AFi - K2XAF2XAF!- - Kn X AFn X AFi-AC X AF^O
A0XAF2- Ki X AFi X AF2- K2XAF2 2 - - Kn X AFn X AF2-AC X AF2=0
A0XAFn- KiXAFiXAFn - K2XAF2XAFn- - KnXAFn 2 -ACXAFn=0
AO-KiXAFi- K2XAF2-…… - KnXAFn-AC=0
求解以上方程组, 得出 K2、 …… Kn、 C。
依次类推, 得出在多组多个像素情况下的 、 K2、 …… Kn、 C。
本发明, 具体实施例中, 将所述传感器阵列中的传感器单元的分组为等分 成至少两组, 同时, 所述传感器阵列中的传感器单元的具体分组方式为: 根据 所述传感器阵列中的传感器单元输出均匀辐射图像的像素值大小, 依次按照像 素值大小将所述传感器阵列中的传感器单元等分成多组。 由于非均匀性图像是 由一部分像素的像素值与另一部分像素的像素值的差异造成的, 若按照像素的 像素值大小排序进行排序分组, 如果有非均匀性的话, 则各组之间的均值必然 存在差异, 在满足校正后图像的每两组像素值的平均值之差的平方和最小的条 件下, 就能将各组之间的非均匀性降到最小, 其得出的校正系数更佳。 本明的
具体实施例中, 所述传感器阵列中的传感器单元的分组中, 所述传感器阵列中 的传感器单元数目为 q, 所述分组数目为 P, 分组满足: q/p 100。在传感器阵 列进行分组过程中, 更佳的效果是必须达到一定数量的分组, 分组过多, 其计 算量大, 因此, 在平衡各方面的情况下, 使其分组满足: q/p 100。
本发明的优选实施方式中, 计算所述各组中像素值的平均值为计算所述各 组中有效像素值的平均值。 有效像素值的判别标准为, 首先计算该组像素的像 素值均值 avg, 然后计算该该组像素的像素值均方差 δ, 设该组像素的像素值为 gray, 若 | gray-avg |〈2δ, 则该像素为有效像素。
如图 2所示, 本发明提供一种非均匀图像校正方法, 所述图像由传感器阵 列输出, 所述传感器阵列包括多个传感器单元, 所述一个传感器单元输出一个 像素值, 采集传感器阵列不同工作温度条件下的多幅背景图像, 所述多幅背景 图像的不同温度条件覆盖所述传感器阵列的工作温度范围, 所述背景图像按所 述传感器阵列中的传感器单元的分组方式进行分组, 获取所述传感器阵列的增 益校正常数, 所述非均匀图像校正方法包括如下步骤:
步骤 10: 获取当前背景图像, gp : 获取当前背景的校正系数, 根据采集的 背景图像和当前背景的校正系数计算出传感器阵列当前工作状态下的背景图 像。 获取图像校正系数的具体方法为上述图像校正系数获取方法进行计算, 在 此不再进行详细的描述。
本发明的具体实施方式中, 坐标为 (x,y) 的当前背景像素值:
offset (x,y ) ^ X F! (x, y ) +K2 X F2 (x, y ) +K3 X F3 (x, y ) +…… +Kn X Fn (x,y) +C, 由于, Id、 K2、 …… Kn、 C通过非均匀图像校正系数的获取方法 得出, (x,y)、 F2 (x,y)、 F3 (x, y) …… Fn (x, y ) 通过采集背景图像得到, 由此,即可得到当前背景图像 offse x, y),通过计算图像的各个像素的 offset (x, y ) ,即可以计算出图像所有像素的 offset。
其中, F2、 F3…… Fn为背景图像, 通过采集背景图像, SP : 采集传感器 阵列输出的不同温度条件下的多幅均匀辐射图像, 所述多幅均匀辐射图像的不 同温度条件覆盖所述传感器阵列的工作温度范围。在本发明的具体实施方式中, 若传感器阵列输出的不同温度条件下的多幅均匀辐射图像为 、 F2、 F3…… Fn, 则背景图像为 、 F2、 F3…… Fn。 本发明具体实施方式中, 所述多幅均匀辐射图 像所在的温度点在所述传感器阵列的工作温度范围内均匀分布。
步骤 20: 获取图像校正结果, gp: 根据非均匀性两点校正公式获取图像校 正结果。
具体实施过程如下: 根据非均匀性两点校正公式: IMG (X, y) =[0 (x, y) - offset (x, y) ] XGain (x, y), 其中, offset (x, y)表示当前坐标为(x, y) 的背景像素值, Gain (x, y) 表示传感器单元坐标为 (x, y) 的增益校正常数, IMG (X, y)表示校正之后坐标为(x,y)的像素值, 0 (x, y)表示坐标为(x, y) 的预校正的像素值。 通过该公式得出图像中所有像素点的校正值, 即得到校正 后的图像。
其中, Gain (x, y) 的获取是根据同一环境温度条件下的两幅不同辐射强 度下的均匀辐射体的图像获取增益校正常数。 本发明的具体实施方式中, 若同 一环境温度条件下的两幅不同辐射强度下的均匀辐射体的图像 BlackH 和 BlackL, 图像增益校正常数 Gain (i, j) 为:
^ ^ BlackH (/, ;) ^ ^ BlackLii, j)
BlackH ( , j) BlackL(j, j) 其中: (i,j)表示图像像素的坐标, w表示图像的行数, h表示图像的列数。
Gain(i、 j)即所述传感器阵列中坐标为(i, j)传感器单元的增益校正常数, 通过计算传感器阵列中各个传感器单元的增益校正常数, 即得到所述传感器阵 列增益校正常数。
本发明非均匀图像校正方法, 通过获取当前背景的校正系数, 根据采集的 背景图像和当前背景的校正系数计算出传感器阵列当前工作状态下的背景图 像, 再根据非均匀性两点校正公式获取图像校正结果。 本发明非均匀图像校正 方法与常规的现有技术相比, 不需要调零挡片。 同时, 不需要强调采用计算相 邻像素的差值, 对位置要求不高, 计算方法简便。
本发明的技术方案是: 构建一种非均匀图像校正***, 包括输出图像的传 感器阵列 2以及图像校正单元 1, 所述传感器阵列 2包括多个传感器单元, 所 述一个传感器单元输出一个像素值, 所述图像校正单元 1包括采集图像的图像 采集模块 11、计算当前背景图像的背景计算模块 13、计算当前背景图像校正系 数的校正系数计算模块 12、 计算增益校正常数的增益校正常数计算模块 14以 及获取图像校正结果的图像获取模块 15, 所述图像采集模块 11采集传感器阵
列输出的不同工作温度条件下的多幅背景图像, 所述多幅背景图像的不同温度 条件覆盖所述传感器阵列的工作温度范围, 所述背景图像按所述传感器阵列中 的传感器单元的分组方式进行分组;所述校正系数计算模块 12计算当前背景图 像的校正系数,所述背景计算模块 13根据采集的背景图像和当前背景图像的校 正系数计算出传感器阵列当前工作状态下的背景图像; 所述增益校正常数模块 14计算所述传感器阵列的增益校正常数; 所述图像获取模块 15根据非均匀性 两点校正公式获取图像校正结果。
本发明的具体工作过程如下:所述图像采集模块 11采集传感器阵列不同工 作温度条件下的多幅背景图像, 所述多幅背景图像的不同温度条件覆盖所述传 感器阵列的工作温度范围。校正系数计算模块 12获取当前背景的校正系数,其 具体获取方法为上述图像校正系数获取方法进行计算, 在此不再进行详细的描 述。
背景计算模块 13 根据采集的背景图像和当前背景的校正系数计算出传感 器阵列当前工作状态下的背景图像。具体过程如下: 坐标为(x,y)的当前背景 像素值:
offset (x,y) = lX¥l (x,y) +K2XF2 (x, y) +K3XF3 (x, y) + KnX
Fn (x,y) +C, 由于, Id、 K2、 …… Kn、 C通过非均匀图像校正系数的获取方法得 出, (x,y)、 F2 (x,y)、 F3 (x, y) …… Fn (x, y) 通过采集背景图像得到, 由 此, 即可得到当前背景图像 offset (x, y),通过计算图像的各个像素的 offset (x, y) ,即可以计算出图像所有像素的 offset。
其中, F2、 F3…… Fn为背景图像, 所述图像采集模块 11通过采集背景 图像, gp: 采集传感器阵列输出的不同温度条件下的多幅均匀辐射图像, 所述 多幅均匀辐射图像的不同温度条件覆盖所述传感器阵列的工作温度范围。 在本 发明的具体实施方式中, 若传感器阵列输出的不同温度条件下的多幅均匀辐射 图像为 、 F2、 F3…… Fn, 则背景图像为 、 F2、 F3…… Fn。 本发明具体实施方式 中, 所述多幅均匀辐射图像所在的温度点在所述传感器阵列的工作温度范围内 均匀分布。
图像获取模块 15根据非均匀性两点校正公式获取图像校正结果。具体实施 过程如下: 根据非均匀性两点校正公式: IMG (X, y) =[0 (x, y) - offset (x, y) ] XGain (x, y), 其中, offset (x, y)表示当前坐标为 (x, y) 的背景像素
值, Gain ( x, y )表示传感器单元坐标为 (x, y ) 的增益校正常数, IMG ( x , y ) 表示校正之后坐标为 (x,y ) 的像素值, 0 ( X , y )表示坐标为 (x,y ) 的预校正 的像素值。通过该公式得出图像中所有像素点的校正值, 即得到校正后的图像。
其中, Gain ( x, y ) 的获取是根据同一环境温度条件下的两幅不同辐射强 度下的均匀辐射体的图像获取增益校正常数。增益校正常数计算模块 14计算所 述传感器阵列 2的增益校正常数,具体过程如下:若同一环境温度条件下的两幅 不同辐射强度下的均匀辐射体的图像 BlackH和 BlackL,图像增益校正常数 Gain
( i, j ) 为:
^ ^ BlackH (/, ;) ^ ^ BlackLii, j)
BlackH ( , j) BlackL(j, j) 其中: (i,j)表示图像像素的坐标, w表示图像的行数, h表示图像的列数。
Gain ( i、 j)即所述传感器阵列 2 中坐标为(i, j)传感器单元的增益校正常 数, 通过计算传感器阵列 2中各个传感器单元的增益校正常数, 即得到所述传 感器阵列 2增益校正常数。
本发明的技术效果是: 提供一种非均匀图像校正***, 通过获取当前背景 的校正系数, 根据采集的背景图像和当前背景的校正系数计算出传感器阵列当 前工作状态下的背景图像, 再根据非均匀性两点校正公式获取图像校正结果。 本发明非均匀图像校正方法与常规的现有技术相比, 不需要调零挡片。 同时, 不需要强调采用计算相邻像素的差值, 对位置要求不高, 计算方法简便。
以上内容是结合具体的优选实施方式对本发明所作的进一步详细说明, 不 能认定本发明的具体实施只局限于这些说明。 对于本发明所属技术领域的普通 技术人员来说, 在不脱离本发明构思的前提下, 还可以做出若干简单推演或替 换, 都应当视为属于本发明的保护范围。
Claims
1.一种图像校正系数的获取方法, 其特征在于, 所述图像由传感器阵列输 出, 所述传感器阵列包括多个传感器单元, 所述一个传感器单元输出一个像素 值, 所述传感器阵列中的传感器单元至少为两组, 采集传感器阵列不同工作温 度条件下的多幅背景图像, 所述背景图像按所述传感器阵列中的传感器单元的 分组方式进行分组, 所述图像校正系数的获取方法包括如下步骤:
将预校正图像分组: 根据所述传感器阵列中的传感器单元的分组, 将所述 传感器阵列输出的预校正图像的像素进行相应分组;
计算当前背景的校正系数: 按组获取所述预校正图像的各像素值, 计算所 述各组中像素值的平均值, 在预校正图像的分组中, 满足校正后图像的每两组 像素值的平均值之差的平方和最小的条件下, 计算出当前背景的校正系数。
2.根据权利要求 1所述图像校正系数的获取方法, 其特征在于, 将所述传 感器阵列中的传感器单元的分组为等分成至少两组。
3.根据权利要求 1或 2所述图像校正系数的获取方法, 其特征在于, 所述 传感器阵列中的传感器单元的分组方式为: 根据所述传感器阵列中的传感器单 元输出均匀辐射图像的像素值大小, 依次按照像素值大小将所述传感器阵列中 的传感器单元等分成多组。
4.根据权利要求 1所述图像校正系数的获取方法, 其特征在于, 采集传感 器阵列不同温度条件下的背景图像, 所述多幅均匀辐射图像的不同温度条件覆 盖所述传感器阵列的工作温度范围。
5.根据权利要求 3所述图像校正系数的获取方法, 其特征在于, 所述传感 器阵列中的传感器单元的分组中, 所述传感器阵列中的传感器单元数目为 q, 所述分组数目为 p, 分组满足: q/p 100。
6.根据权利要求 1所述图像校正系数的获取方法, 其特征在于, 在计算出 图像校正系数步骤中, 计算所述各组中像素值的平均值为计算所述各组中有效 像素值的平均值。
7.—种非均匀图像校正方法, 其特征在于, 所述图像由传感器阵列输出, 所述传感器阵列包括多个传感器单元, 所述一个传感器单元输出一个像素值, 采集传感器阵列不同工作温度条件下的多幅背景图像, 所述多幅背景图像的不 同温度条件覆盖所述传感器阵列的工作温度范围, 所述背景图像按所述传感器 阵列中的传感器单元的分组方式进行分组, 获取所述传感器阵列的增益校正常 数, 所述非均匀图像校正方法包括如下步骤:
获取当前背景图像: 获取当前背景的校正系数, 根据采集的背景图像和当 前背景的校正系数计算出传感器阵列当前工作状态下的背景图像。
获取图像校正结果: 根据非均匀性两点校正公式获取图像校正结果。
8.根据权利 7所述的非均匀图像校正方法, 其特征在于, 所述多幅背景图 像的不同温度条件均匀覆盖所述传感器阵列的工作温度范围。
9.一种非均匀图像校正***, 其特征在于, 包括输出图像的传感器阵列以 及图像校正单元, 所述传感器阵列包括多个传感器单元, 所述一个传感器单元 输出一个像素值, 所述图像校正单元包括采集图像的图像采集模块、 计算当前 背景图像的背景计算模块、 计算当前背景图像校正系数的校正系数计算模块、 计算增益校正常数的增益校正常数计算模块以及获取图像校正结果的图像获取 模块, 所述图像采集模块采集传感器阵列输出的不同工作温度条件下的多幅背 景图像, 所述多幅背景图像的不同温度条件覆盖所述传感器阵列的工作温度范 围, 所述背景图像按所述传感器阵列中的传感器单元的分组方式进行分组; 所 述校正系数计算模块计算当前背景图像的校正系数, 所述背景计算模块根据采 集的背景图像和当前背景图像的校正系数计算出传感器阵列当前工作状态下的 背景图像; 所述增益校正常数模块计算所述传感器阵列的增益校正常数; 所述 图像获取模块根据非均匀性两点校正公式获取图像校正结果。
10.根据权利要求 9所述的非均匀图像校正***,其特征在于,所述多幅背 景图像的不同温度条件均匀覆盖所述传感器阵列的工作温度范围。
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