Color Correction

Color correction addresses issues like incorrect white balance, color casts from mixed lighting sources, faded colors in old photographs, and oversaturation from camera processing. The goal is making colors look accurate to the original scene as perceived by the human eye. This differs from color grading, which intentionally shifts colors for creative or stylistic effect. Color correction is a technical adjustment; color grading is an artistic choice. Both are common in professional workflows, but correction typically comes first.\n\nFood photographers rely on accurate color correction to make dishes look appetizing. A photo taken under restaurant fluorescent lighting may give the food a greenish tint that makes it look unappetizing. Color correction removes the green cast, restores warm tones to the bread crust, and ensures the red of tomato sauce looks natural. Without color correction, technically well-composed food photos can fail to achieve their intended impact.\n\nManual color correction requires understanding color theory and the relationship between complementary colors. A yellow color cast is corrected by adding blue. A magenta cast is corrected by adding green. Experienced editors use tools like curves, levels, and HSL (hue, saturation, luminance) sliders to target specific colors without affecting others. This skill takes time to develop and varies with experience.\n\nMagic Eraser's AI Enhance performs automatic color correction by analyzing the image for color casts, white balance errors, and saturation issues. The AI identifies neutral reference points in the image, determines what adjustments are needed, and applies corrections that produce natural-looking colors without any manual parameter adjustment. This automatic correction is especially valuable for users editing photos from events with mixed lighting, outdoor scenes with strong color casts from foliage or water reflections, and old photographs where colors have shifted due to chemical degradation of the original print or negative over time.