He Dongjian - Color Bitmap to Black-and-White Bitmap Conversion Code

Converting color bitmaps to black-and-white bitmaps represents a fundamental operation in image processing, commonly referred to as grayscale conversion. The code provided by He Dongjian likely employs a classical transformation method that converts RGB components of color pixels into single grayscale values through weighted averaging or fixed formulas, thereby generating black-and-white (grayscale) images. Implementation approach analysis: Pixel traversal: The code likely begins by reading each pixel of the original color bitmap, extracting its Red (R), Green (G), and Blue (B) component values. Grayscale formulas: Common conversion methods include: Weighted average method: Accounting for human eye sensitivity variations to different colors, using `Gray = 0.299*R + 0.587*G + 0.114*B` to calculate grayscale values. Average method: Directly computing the arithmetic mean of RGB components using `(R+G+B)/3`. Binarization (optional): For pure black-and-white results (non-grayscale), the implementation may include thresholding to convert grayscale values to either 0 (black) or 255 (white). Output processing: The generated grayscale or binary data is written to a new bitmap file to complete the conversion. Technical extensions: Optimization directions: Can incorporate brightness/contrast adjustments or utilize error diffusion algorithms (like Floyd-Steinberg) to enhance visual quality. Application scenarios: Such conversions are frequently required in document scanning, OCR preprocessing, and simplified image analysis applications. (Note: Specific implementation details require reference to the original code; only general logic is described here.)