This chapter explores pixel operations, also known as point transformations, which are fundamental techniques in digital image processing where each pixel is modified independently based on its intensity value. It begins by distinguishing between homogeneous and inhomogeneous transformations, explaining how brightness, contrast, and inversion adjustments alter pixel values through simple mathematical mappings. The chapter introduces essential concepts such as clamping to prevent overflow or underflow in pixel intensity and demonstrates practical implementations in Python and OpenCV. Additionally, it addresses composite pixel transformations, where corresponding pixels from multiple images are combined using arithmetic, logical (AND/OR), or alpha blending operations to achieve effects such as motion detection, image fusion, or transparency control. Overall, the chapter provides both the theoretical foundation and practical implementation of pixel-level processing, highlighting its importance in computer vision, image enhancement, and preprocessing applications.