MSRCR Image Enhancement Algorithm Based on Retinex Theory

This implementation provides a fully functional source code for the MSRCR (Multi-Scale Retinex with Color Restoration) image enhancement algorithm based on Retinex theory. The code has undergone comprehensive testing and is production-ready for immediate use. This algorithm significantly improves image quality by enhancing detail visibility and contrast through its multi-scale processing approach and color preservation mechanism. The implementation demonstrates practical application of the core MSRCR algorithm which operates by: estimating illumination components at multiple scales (typically using Gaussian filters with different sigma values), computing reflectance components, and applying color restoration to maintain natural color appearance. Whether you're a professional image processing engineer or an enthusiast interested in computational photography, this source code offers valuable implementation insights. It supports processing various image types including photographs, digital artworks, scanned documents, and printed materials. The clean code structure allows straightforward integration - simply input your image data and receive enhanced output. Key functions include: multi-scale Gaussian convolution, logarithmic domain processing, and color restoration components. Test the implementation to observe significant improvements in image clarity and dynamic range optimization!