Image Filtering and Enhancement

Image filtering and enhancement are fundamental techniques in computer vision that aim to improve the quality of images. Image filtering is the process of modifying an input image by applying a specific algorithm to its pixels. The purpose of image filtering is to remove noise, sharpen an image, or blur an image. Image enhancement is the process of improving the quality of an image by increasing its contrast, brightness, or sharpness. These techniques are widely used in applications such as medical imaging, satellite imaging, and surveillance systems.

Types of Filters

Image filtering can be performed using different types of filters, such as:

• Mean filters
• Median filters
• Gaussian filters

Mean filters replace each pixel value with the average of the neighboring pixel values. Median filters replace each pixel value with the median of the neighboring pixel values. Gaussian filters use a Gaussian function to compute the weighted average of the neighboring pixel values.

Achieving Image Enhancement

Image enhancement can be achieved by adjusting the:

• Brightness: increases or decreases the overall brightness of an image.
• Contrast: changes the difference between the brightest and darkest parts of an image.
• Sharpness: increases the contrast between the edges in an image.

In computer vision, image filtering and enhancement are used in a wide range of applications. For example, in facial recognition systems, image filtering is used to remove noise and enhance facial features. In autonomous vehicles, image enhancement is used to improve the visibility of objects in low-light conditions. In medical imaging, image filtering is used to remove artifacts and enhance the contrast between tissues.

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