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基于高動(dòng)態(tài)范圍成像的溫室番茄植株圖像色彩矯正方法
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國家自然科學(xué)基金項(xiàng)目(61703048)、北京市農(nóng)林科學(xué)院青年科研基金項(xiàng)目(QNJJ201722)和江蘇大學(xué)農(nóng)業(yè)裝備學(xué)部項(xiàng)目(4111680002)


Image Color Correction Method for Greenhouse Tomato Plant Based on HDR Imaging
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    摘要:

    針對(duì)溫室番茄智能化管理視覺信息穩(wěn)定獲取的需要,研究了基于高動(dòng)態(tài)范圍成像技術(shù)的番茄植株圖像色彩矯正方法,以克服復(fù)雜自然光照條件對(duì)作業(yè)對(duì)象色彩穩(wěn)定呈現(xiàn)的客觀限制。鑒于溫室內(nèi)光照時(shí)空波動(dòng)和復(fù)雜背景輻射強(qiáng)度突變導(dǎo)致圖像色彩失真,提出了融合多曝光強(qiáng)度圖像的攝像機(jī)輻射響應(yīng)模型標(biāo)定方法;分別提取曝光時(shí)間為0.01、0.05、0.08、0.10ms的4幅圖像離散像素點(diǎn)的Y通道亮度信息,求解特定視場(chǎng)下像素點(diǎn)亮度與曝光度的函數(shù)關(guān)系,在此基礎(chǔ)上以低曝光度圖像亮度為參考,估計(jì)攝像機(jī)全局視場(chǎng)的輻射強(qiáng)度;采用S曲線函數(shù)壓縮高動(dòng)態(tài)范圍圖像數(shù)據(jù),將視場(chǎng)輻射強(qiáng)度映射為圖像亮度,實(shí)現(xiàn)對(duì)低曝光圖像的色彩矯正重構(gòu);最后,通過現(xiàn)場(chǎng)試驗(yàn)對(duì)色彩矯正方法進(jìn)行驗(yàn)證,試驗(yàn)結(jié)果表明,不同場(chǎng)景和時(shí)段的番茄植株圖像的灰度信息量、離散程度和清晰度均得到改善,圖像灰度信息熵、標(biāo)準(zhǔn)方差和平均梯度平均提高16.87%、9.81%和19.49%。本研究可為農(nóng)業(yè)復(fù)雜光照條件下作業(yè)對(duì)象圖像色彩信息的獲取研究提供參考。

    Abstract:

    In order to accurately acquire the tomato plants’ image information under the complex illumination in greenhouse, the method of correcting image color based on high dynamic range (HDR) imaging was researched, which was urgently needed for robotic production in greenhouse. Focused at the color distortion caused from sunlight’s continuous variation and background object’s radiation saltation, the color image’s brightness data was extracted from CIE XYZ color mode. And the camera’s response function was recovered, according to the brightness images with various exposure time of 0.01ms, 0.05ms,0.08ms and 0.10ms. As the HDR image data, the radiation intensity of the view field was estimated based on the response function, referring to the underexposed image’s brightness. The HDR brightness data was compressed into brightness image with grey value range of (0, 255), by the S-shaped mapping function, and then the brightness data was integrated into the underexposed image to reconstruct the image color data. Finally, the color correction method was verified by field test in greenhouse. As the result showed, the method was applicative for improving color quality of images, captured from different scenes under the various sunlight at different time. Specifically, the image’s entropy, standard deviation, and average gradient were averagely raised by 16.87%, 9.81% and 19.49%, respectively, after the original images captured with the serial exposure time were fused, and the color of image captured at different time could keep stable. The research result was supposed as the reference for acquiring object image information under the complex agricultural environment.

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馮青春,王秀,李軍輝,李小明,成偉,陳建.基于高動(dòng)態(tài)范圍成像的溫室番茄植株圖像色彩矯正方法[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2020,51(11):235-242. FENG Qingchun, WANG Xiu, LI Junhui, LI Xiaoming, CHENG Wei, CHEN Jian. Image Color Correction Method for Greenhouse Tomato Plant Based on HDR Imaging[J]. Transactions of the Chinese Society for Agricultural Machinery,2020,51(11):235-242.

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  • 收稿日期:2020-02-17
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  • 在線發(fā)布日期: 2020-11-10
  • 出版日期: 2020-11-25
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