Multi-Frame Image Super-Resolution Reconstruction Algorithm Based on L2 Norm

The L2-norm-based multi-frame image super-resolution reconstruction algorithm enhances computational accuracy and efficiency compared to existing methods.

Improving computational precision and efficiency constitutes the core objective of this research. Our study builds upon existing algorithms and introduces novel L2-norm-based methodologies. By utilizing multiple image frames, we achieve enhanced super-resolution performance and superior image reconstruction quality. The algorithm improvements focus on optimizing matrix inversion operations through conjugate gradient methods and implementing regularization techniques that minimize the L2-norm of reconstruction errors. These enhancements are implemented via parallel computing architecture to handle large-scale image data efficiently. Experimental results validate the effectiveness of our approach, demonstrating significant reductions in computational complexity while maintaining reconstruction accuracy. These advancements contribute to the progression of image processing technologies, providing more efficient solutions for high-quality image reconstruction applications.