1. 毕业设计（论文）的内容、要求、设计方案、规划等
多光谱图像预处理质量的高低很大程度上限制了后续处理的成败与效果。
本课题旨在借助图像处理软件工具，对采集到的多光谱图像进行降噪预处理。
以期达到理想的图像质量。
2. 参考文献（不低于12篇）
《数字图像处理》，冈萨雷兹，电子工业出版社，2002A. Al-MallahiKataoka, H. OkamotoT. (2008). Discrimination between potato tubers and clods by detecting the significant wavebands. Biosystems Engineering, 100 (3), 329-337.Alan M. LefcoutS. Kim, Yud-Ren Chen, Sukwon KangMoon. (2006). Systematic approach for using hyperspectral imaging data to develop multispectral imagining systems: Detection of feces on apples. Computers and Electronics in Agriculture, 54 (1), 22-35.Alan M. LefcoutS. KimMoon. (2006). Technique for normalizing intensity histograms of images when the approximate size of the target is known: Detection of feces on apples using fluorescence imaging. Computers and Electronics in Agriculture, 50 (2), 135-147.Alexander F.H. GoetzVane, Jerry E. Solomon, and Barrett N. RockGregg. (1985). Imaging Spectrometry for Earth Remote Sensing. Science, 228 (4704), 1147 - 1153.Aoife A. GowenTaghizadeh, Colm P. ODonnellMasoud. (July 2009). Identification of mushrooms subjected to freeze damage using hyperspectral imaging. Journal of Food Engineering, 93 (1), 7-12.B. ParkWindham, K.C. Lawrence, D.P. SmithW.R. (2007). Contaminant Classification of Poultry Hyperspectral Imagery using a Spectral Angle Mapper Algorithm. Biosystems Engineering, 96 (3), 323-333.Bosoon ParkC. Lawrence, William R. Windham, Douglas P. SmithKurt. (2006). Performance of hyperspectral imaging system for poultry surface fecal contaminant detection. Journal of Food Engineering, 75 (3), 340-348.Byoung-Kwan ChoChen, Moon S. KimYud-Ren. (2007). Multispectral detection of organic residues on poultry processing plant equipment based on hyperspectral reflectance imaging technique. Computers and Electronics in Agriculture, 57 (2), 177-189.G. W. HeitschmidtPark, K. C. Lawrence, W. R. Windham, D. P. SmithB. (2007). Improved Hyperspectral Imaging System for Fecal Detection on Poultry Carcasses. Transactions of the ASABE, 50 (4), 1427-1432.Govindarajan Konda NaganathanM. Grimes, Jeyamkondan Subbiah, Chris R. Calkins, Ashok Samal, George E. MeyerLauren. (2008). Visible/near-infrared hyperspectral imaging for beef tenderness prediction. Computers and Electronics in Agriculture, 64 (2), 225-233.J. BlascoJ.Go′mez, E. MoltoN.Aleixos,. (2007). Citrus sorting by identification of the most common defects using multisectral computer vision. Journal of Food Engineering, 83, 384-393.J. Gmez-SanchisGmez-Chova, N. Aleixos, G. Camps-Valls, C. Montesinos-Herrero, E. Molt, J. BlascoL. (2008). Hyperspectral system for early detection of rottenness caused by Penicillium digitatum in mandarins. Journal of Food Engineering, 89 (1), 80-86.J. Gmez-SanchisMolt, G. Camps-Valls, L. Gmez-Chova, N. Aleixos, J. BlascoE. (2008). Automatic correction of the effects of the light source on spherical objects. An application to the analysis of hyperspectral images of citrus fruits. Journal of Food Engineering, 85 (2), 191-200.J. QiaoWang, M.O. Ngadi, A. Gunenc, M. Monroy, C. Garipy, S.O. PrasherN. (2007). Prediction of drip-loss, pH, and color for pork using a hyperspectral imaging technique. Meat Science, 76 (1), 1-8.JohnsonE.Dallase. (2005). Independence of Experimental Units. 出处 JohnsonE.Dallase, Applied Multivariate Methods for Data Analysts 应用多元统计分析方法（影印版） (页 11). 北京: 高等教育出版社.Juan XingSaeys, Josse De BaerdemaekerWouter. (2007). Combination of chemometric tools and image processing for bruise detection on apples. Computers and Electronics in Agriculture, 56 (1), 1-13.Jun QiaoO. Ngadi, Ning Wang, Claude Garipy, Shiv.O. PrasherMichael. (2007). Pork quality and marbling level assessment using a hyperspectral imaging system. Journal of Food Engineering, 83 (1), 10-16.K. C. LawrencePark, G. W. Heitschmidt W. R. Windham, C. N. ThaiB. (2007). Evaluation of LED and Tungsten-Halogen Lighting for Fecal Contaminant Detection. Applied Engineering in Agriculture, 23 (6), 811-818.L. LleBarreiro, M. Ruiz-Altisent, A. HerreroP. (2009). Multispectral images of peach related to firmness and maturity at harvest. Journal of Food Engineering, 93 (2), 229-235.LawrencePark, B., Windham, W.R., Mao, C.K.C.,. (2003). Calibration of a pushbroom hyperspectral imaging system foragricultural inspection. Transactions of the ASAE, 46 (2), 513521.LawrenceWindham, W.R., Park, B., Heitschmidt, G.W.,Smith, D.P., Feldner, P.K.C.,. (2006). Partial least squares regression of hyperspectral images for contaminant detection on poultry carcasses. Journal of Near Infrared Spectroscopy, 14, 223230.LuRenfu. (2004). Multispectral imaging for predicting firmness and soluble solids content of apple fruit. Postharvest Biology and Technology, 31 (2), 147-157.M. S. KimM. Lefcourt, K. Chao, Y. R. Chen, I. Kim, D. E. ChanA. (2002). Multispectral Detection of Fecal Contamination on Apples Based on Hyperspectral Imagery: Part I. Application of Visible and Near/Infrared Reflectance Imaging. Transactions of the ASAE, 45 (6), 2027-2037.M. S. KimM. Lefcourt, Y. R. Chen, I. Kim, D. E. Chan, K. ChaoA. (2002). Multispectral Detection of Fecal Contamination on Apples Based on Hyperspectral Imagery: Part II. Application of Hyperspectral Fluorescence Imaging. Transactions of the ASAE, 45 (6), 2039-2047.S. C. YoonC. Lawrence, B. Park, W. R. WindhamK. (2007). Optimization of Fecal Detection Using Hyperspectral Imaging and Kernel Density Estimation. Transactions of the ASABE, 50 (3), 1063-1071.S. C. YoonC. Lawrence, B. Park, W. R. WindhamK. (2007). Statistical Model-Based Thresholding of Multispectral Images for Contaminant Detection on Poultry Carcasses. Transactions of the ASABE, 50 (4), 1433-1442.Songyot NakariyakulP. CasasentDavid. (October 2009). Fast feature selection algorithm for poultry skin tumor detection in hyperspectral data. Journal of Food Engineering, 94 (3-4), 358-365.Y. PengLuR. (2006). An LCTF-Based Multispectral Imaging System for Estimation of Apple fruit Firmness: Part I. Acquisition and Characterization of Scattering Images. Transactions of the ASABE, 49 (1), 269-275.Y. PengLuR. (2006). An LCTF-Based Multispectral Imaging System for Estimation of Apple Fruit Firmness: Part II. Selection of Optimal Wavelengths and Development of Prediction Models. Transactions of the ASABE, 49 (1), 269-275.田海清陆辉山, 徐惠荣, 谢丽娟应义斌,. (2009). 基于可见/近红外光谱的乙烯利催熟西瓜与正常成熟西瓜分类试验研究. 光谱学与光谱分析(04), 940-944.
以上是毕业论文任务书，课题毕业论文、开题报告、外文翻译、程序设计、图纸设计等资料可联系客服协助查找。
