What is image statistics? Explain the univariate and multivariate image statistics in detail.

Image statistics refer to the methods and techniques used to describe, analyze, and summarize the features or properties of an image based on its pixel intensities or colors. These statistical measures help in understanding the patterns, textures, distributions, and structures present in an image. Image statistics can be broadly divided into two categories: univariate and multivariate, each providing different levels of complexity and insight into the data.

### Univariate Image Statistics

Univariate image statistics refer to the analysis of a single channel or component of an image, such as a grayscale image where each pixel has a single intensity value. The focus here is on examining the distribution of pixel intensities across the entire image or within a specific region of interest. Univariate statistics often involve the calculation of simple measures such as the following:

1. Mean (Average): The mean intensity value of the pixels in the image is a fundamental measure of the overall brightness or darkness of the image. It is calculated by summing all pixel values and dividing by the number of pixels.

2. Variance and Standard Deviation: Variance measures the spread or dispersion of pixel __________ __________ ________ ______ _________ _______.
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