| Sumario: | This study investigates developing and optimizing hybrid algorithms for image processing and encryption using numerical optimization techniques based on heat diffusion methods. Using finite difference methods, we show the application to different types of images, which will be converted into arrays and treated as coefficients in the computational process. The paper aims to enhance image quality through algorithmic optimization and hybridization strategies. Experiments in one and two dimensions are conducted using both explicit and implicit methods to evaluate the impact of these techniques on image processing. The performance of the proposed approach is analyzed using statistical metrics such as Peak Signal-to-Noise Ratio (PSNR), Mean Squared Error (MSE), Maximum Difference (MD), and additional quality assessment parameters.
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