J.-Q. Tang

Optimization of Methods for Restoring Motion-Coded Blurred Images Based on Deep Residual Networks

An optimized restoration framework based on deep residual networks that incorporates a multi-scale residual learning architecture, enhanced skip-connection mechanisms, and a channel attention module to improve blur feature representation, training efficiency, and color information utilization is proposed.