MATLAB Code Implementation for Red-Eye Removal

MATLAB implementation of manual red-eye removal typically involves interactive image editing and color correction techniques. Here's the typical implementation approach for this functionality: First, users need to load a photo containing red-eye effects. MATLAB's Image Processing Toolbox provides interactive tools that allow users to manually select red-eye regions, typically by drawing rectangular or free-form selections. The selection operation implementation relies on graphical interface callback functions that track mouse movements in real-time and mark target areas through event handling mechanisms. After selecting the region, the system extracts RGB color information from the affected area. Red-eye is essentially the reflection of retinal blood vessels under flash photography, manifesting as highly saturated red pixels. During processing, the image is typically converted from RGB to HSV or YCbCr color space using functions like rgb2hsv(), which facilitates separation of chrominance and luminance components for precise identification of abnormal red regions. The core correction algorithm applies hue shifting and brightness adjustments to pixels within the selected area: reducing red channel intensity while simultaneously increasing blue/green channel values to restore pupils to natural black or dark brown. Some implementations incorporate local threshold segmentation using functions like imbinarize() or multithresh(), modifying only excessively red pixels that exceed normal color gamut to avoid over-processing. Users can adjust red-eye removal intensity and feathering range parameters through slider controls, with real-time preview capabilities. The final output seamlessly integrates corrected pixels back into the original image using alpha blending techniques, with Gaussian blur applied at boundaries to eliminate harsh transitions through functions like imgaussfilt(). The entire process combines computer vision techniques with interactive design, balancing processing accuracy and operational flexibility through MATLAB's comprehensive image processing workflow.