Having established how digital images are represented numerically, we now shift focus to modifying and enhancing these representations. Basic image processing operations are fundamental tools in computer vision, used for tasks ranging from improving image quality to preparing images for more complex analysis like feature detection.

In this chapter, you will learn several foundational image processing techniques:

• Point Operations: Adjusting the brightness and contrast of an image by modifying individual pixel values.
• Image Histograms: Understanding and utilizing histograms to visualize the distribution of pixel intensities, including using histogram equalization for automatic contrast enhancement.
• Geometric Transformations: Performing operations like scaling (resizing), rotation, and translation (shifting) on images.
• Image Filtering: Introducing the concept of using kernels (small matrices) to modify pixel values based on their neighbors, focusing on basic smoothing filters (like Average and Gaussian) to reduce noise.

We will cover the concepts behind these techniques and demonstrate how to implement them using common libraries, concluding with hands-on practice applying these transformations.