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Chemometric methods applied in the image plane to correct striping noise in hyperspectral chemical images of biomaterials

机译：化学计量方法应用于图像平面以校正生物材料的高光谱化学图像中的校正条纹噪声

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Abstract > Array detectors improve data collection speed in hyperspectral chemical imaging, yet are prone to striping noise patterns in the image plane, which is difficult to remove. This type of noise affects spectral features and disturbs visual impression of the scene. We found that this type of noise depends on the material composition and setting parameters, ie, pixel size, and it also varies in accordance with the signal intensity of the observed wavelength. To address this, we proposed a new correction method on the basis of the application of chemometric techniques in the image plane of each wavelength. To verify the effectiveness of this method, infrared transmission images of the 2″?×?2″ positive, 1951 USAF Hi‐Resolution Target and biomaterial samples were obtained with a 16‐element ( type="mathematics">8?×?2 ) pixel array detector. Point detector images of some samples were also acquired and used as reference images. The proposed correction method produced substantial improvements in the visual impression of intensity images. Principal components analysis was performed to inspect spectral changes after preprocessing, and the results suggested that the major spectral features were not altered while the stripes on intensity images were removed. Spectral profiles and principal components analysis loadings inspection confirmed the smoothing ability of this correction method. As traditional preprocessing techniques, standard normal variate and derivative transformation were not able to remove line artifacts, especially on the biomaterial images. Overall, the proposed method was effective for removing striping noise patterns from infrared images with a minimal alteration of the valuable hyperspectral image information. </abstract> </span> <span class="z_kbtn z_kbtnclass hoverxs" style="display: none;">展开▼</span> </div> <div class="translation abstracttxt"> <span class="zhankaihshouqi fivelineshidden" id="abstract"> <span>机译：</span><Abstract XMLNS =“http://www.wiley.com/namespaces/wiley”type =“main”xml：lang =“en”> <标题类型=“main”>抽象</ title> > 阵列探测器提高高光谱化学成像中的数据收集速度，但易于在图像平面中的噪声模式，这难以去除。这种类型的噪声影响光谱特征和扰乱场景的视觉印象。我们发现这种类型的噪声取决于材料组成和设置参数，即像素尺寸，并且它也根据观察到的波长的信号强度而变化。为了解决这一点，我们提出了一种新的校正方法，基于在每个波长的图像平面中的应用化学测量技术的应用。为了验证该方法的有效性，用16元件获得2“×β2”阳性，1951USAF高分辨率靶和生物材料样品的红外透射图像。 <跨度类型=“数学”> 8？×2 </ span> ）像素阵列检测器。还获取一些样本的点检测器图像并用作参考图像。所提出的校正方法在强度图像的视觉印象中产生了大量的改进。在预处理后进行主成分分析以检查光谱变化，结果表明，在拆除强度图像上的条纹时未改变主要光谱特征。光谱分布和主成分分析负载检查确认了这种校正方法的平滑能力。作为传统的预处理技术，标准正常变化和衍生物转化不能去除线伪像，尤其是在生物材料上。总的来说，所提出的方法对于从红外图像中移除条带噪声模式有效，其具有有价值的高光谱图像信息的最小变化。 </ p> </摘要> </span> <span class="z_kbtn z_kbtnclass hoverxs" style="display: none;">展开▼</span> </div> </div> <div class="record"> <h2 class="all_title" id="enpatent33" >著录项</h2> <ul> <li> <span class="lefttit">来源</span> <div style="width: 86%;vertical-align: text-top;display: inline-block;"> <a href='/journal-foreign-33917/'>《Journal of Chemometrics》</a> <b style="margin: 0 2px;">|</b><span>2018年第4期</span><b style="margin: 0 2px;">|</b><span>共18页</span> </div> </li> <li> <div class="author"> <span class="lefttit">作者</span> <p id="fAuthorthree" class="threelineshidden zhankaihshouqi"> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Xu Jun‐Li&option=202" target="_blank" rel="nofollow">Xu Jun‐Li;</a> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Sun Da‐Wen&option=202" target="_blank" rel="nofollow">Sun Da‐Wen;</a> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Gowen Aoife A.&option=202" target="_blank" rel="nofollow">Gowen Aoife A.;</a> </p> <span class="z_kbtnclass z_kbtnclassall hoverxs" id="zkzz" style="display: none;">展开▼</span> </div> </li> <li> <div style="display: flex;"> <span class="lefttit">作者单位</span> <div style="position: relative;margin-left: 3px;max-width: 639px;"> <div class="threelineshidden zhankaihshouqi" id="fOrgthree"> <p>School of Biosystems and Food EngineeringUniversity College Dublin National University of IrelandBelfield Dublin 4 Ireland;</p> <p>School of Biosystems and Food EngineeringUniversity College Dublin National University of IrelandBelfield Dublin 4 Ireland;</p> <p>School of Biosystems and Food EngineeringUniversity College Dublin National University of IrelandBelfield Dublin 4 Ireland;</p> </div> <span class="z_kbtnclass z_kbtnclassall hoverxs" id="zhdw" style="display: none;">展开▼</span> </div> </div> </li> <li > <span class="lefttit">收录信息</span> <span style="width: 86%;vertical-align: text-top;display: inline-block;"></span> </li> <li> <span class="lefttit">原文格式</span> <span>PDF</span> </li> <li> <span class="lefttit">正文语种</span> <span>eng</span> </li> <li> <span class="lefttit">中图分类</span> <span><a href="https://www.zhangqiaokeyan.com/clc/159.html" title="化学">化学;</a></span> </li> <li class="antistop"> <span class="lefttit">关键词</span> <p style="width: 86%;vertical-align: text-top;"> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=biomaterial&option=203" rel="nofollow">biomaterial;</a> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=chemometrics&option=203" rel="nofollow">chemometrics;</a> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=FTIR&option=203" rel="nofollow">FTIR;</a> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=image analysis&option=203" rel="nofollow">image analysis;</a> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=striping noise&option=203" rel="nofollow">striping noise;</a> </p> <div class="translation"> 机译：生物材料;化学计量学;FTIR;图像分析;条纹噪声; 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