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Image statistics refers to the quantitative description and analysis of the pixel values in a digital image. In remote sensing and digital image processing, image statistics provide essential information about the distribution, structure, and characteristics of the data captured by sensors. They help in understanding the quality of the image, enhancing image features, classifying land cover, and detecting changes in the observed scene. By analyzing the statistical properties of images, it is possible to extract meaningful information that can aid in applications such as environmental monitoring, urban planning, agriculture, and geological studies. Univariate image statistics involve the analysis of individual bands of an image independently. Each band in a remote sensing image represents a particular wavelength or spectral range, and univariate statistics focus on examining the characteristics of a single band without considering its relationship with other bands. The primary components of univariate statistics include measures such as mean, variance, standard deviation, skewness, and kurtosis. The mean of a band provides the average brightness value of all pixels and indicates the overall intensity level. Variance measures the dispersion of pixel values around _______ ___ _________ ____ ______ _____ _____ _____ _____ ____.
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