GB-LSR: Local Spectral Decoding with a Learned Global Bandwidth for Arbitrary-Scale Super-Resolution
GB-LSR introduces a fixed-grid local spectral representation for continuous image reconstruction using a single trainable global scalar bandwidth. This method outperforms existing baselines by achieving better quality while significantly reducing inference cost, making it effective for both native and arbitrary-scale super-resolution tasks.