Theoretical Foundations of Color Processing with Code Implementation

This documentation provides detailed explanations of the source code implementing theoretical foundations of color processing to help readers better understand and master relevant techniques. First, we explore concrete implementation methods for grayscale conversion and pseudo-color processing, including algorithms for transforming images to monochrome format and using pseudo-color mapping to enhance visual effects. Second, we introduce color adjustment methodologies covering techniques for modifying hue, saturation, and brightness parameters, along with implementation approaches for curve-based adjustments enabling finer control. Furthermore, we delve into the principles and implementation strategies for brightness/contrast modification, analyzing their impact on image quality. Subsequently, we examine color quantization and reduction technologies in detail, including methods for reducing color depth to minimize file size while discussing various reduction algorithms and their comparative advantages. Additionally, we demonstrate dithering technique implementations and explain how enhanced CDib classes can further improve image quality and processing effects, providing readers with comprehensive understanding of color processing workflows.