Innovative Color Image Processing Based on Multilayer Memristive Cellular Neural Models

In this research, we present a novel method for color image edge extraction by integrating memristor technology and a multilayer memristive cellular neural network. Our approach converts images from RGB to HSV color space to enhance edge detection precision and robustness. The memristive cellular neural network is implemented by combining memristors with a multilayer cellular neural network in software using MATLAB. To evaluate edge detection accuracy, we use performance metrics such as PSNR and SSIM. For some of the test images, our method achieved a PSNR value of 11.5359 and an SSIM value of 0.5648, which are significantly higher than those of traditional methods. This innovative methodology offers new insights and solutions in image processing and has broad application potential. Specific examples include applications in medical imaging for enhancing the clarity of organ boundaries in color images, in satellite imagery for more accurate detection of geographical features, and in industrial inspection for identifying defects on colored surfaces.