These above problems, which are very important and valuable in agricultural crops area monitoring, are currently less researched. Hence, in this paper, seven types of common texture and five vegetation indices were respectively added into TM multispectral bands to classify using three different methods, which are Minimum Distance, Maximum Likelihood and Support Vector Machine, and analyze the effect on winter wheat identification accuracy by comparing the classification results. The contexture include Mean, Variance, Homogeneity, Contrast, Dissimilarity, Entropy, Variance, Angular Second Moment and Correlation, and the vegetation indices are RVI, SAVI, RDVI, NDWI and SLAVI.

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First scanning the known handwriting materials then number them ,In pretreatment, we convert the valid part of the image into a standard size, as images carries out duotone and go throw off chirp handling in order to achieve better effect.draw features from the known handwriting materials with the Co-occurence,especially,we divided a copy of handwriting into 25 little pieces with the size of 128*128 ,drawing features from every little piecese with four directions(0 degree, 45 degrees, 90 degrees as well as 135 degrees) and calculate the four major feature values( veins and the statistical quantity of veins contrast and the statistical quantity of veins consistency Shang the statistical quantity of statistical quantity as well as the veins correlation of gray scale ), preservation all the feature value that drawn from all known ma terials to the handwriting characteristic database,then input the unknown handwriting materials, also using the method of the Co-occurence to draw those features, recycling the minimum European Distance law match the unknown writing material feature value with the handwriting characteristic feature database, export the label of the known hand writing materials which is most similar to the unknown material with minimum European Distance, and then we can confirm who is the author of the unknown material.

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The results showed that there were significant differences among parameters of texture feature of the different land utilization. In the desertification, the mean and variance were comparatively high. The gray level was asymmetry, the contrasts between neighboring pixels were significant; while in water and irrigable land, the mean, variance was a little bit low, the grey level was symmetry; the mean, variance and gray level in the forest and dry land was between the above (desertification and water and irrigable land).

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high-contrast anomalies：高對比度異常

high-consistency viscometer 高稠度粘度計(jì) | high-contrast anomalies 高對比度異常 | high-contrast image 強(qiáng)反差圖象

Clarity：清晰度

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negative color film：彩色度片

negative birefringence 負(fù)雙折射 | negative color film 彩色度片 | negative contrast 負(fù)反差

contraction crack：縮裂

contraction cavity 縮空 | contraction crack 縮裂 | contrast 對比度,反差,襯度

contrast rendition：反差再現(xiàn),反襯度重現(xiàn)

contrast rendering factor 輝度対比係數(shù) | contrast rendition 反差再現(xiàn),反襯度重現(xiàn) | contrast reversal 反差反轉(zhuǎn)

high-cut filter：高阻濾波器

high-contrast image 強(qiáng)反差圖象 | high-cut filter 高阻濾波器 | high-definition image 高清楚度圖象

acutance：銳度

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Classical Soft Focus：古典柔焦

Solarization Color過曝 | Classical Soft Focus古典柔焦 | Contrast Only反差度