Spatial Image Steganalysis Using Fixed SRM Preprocessing and SRNet

1. A fixed 30-filter SRM preprocessing stage integrated into an SRNet-style backbone, replacing the learned front-end with handcrafted spatial residual filters.

2. Both configurations (BOSSBase alone and a combined BOSSBase+BOWS2 corpus ) are evaluated against SRNet and ResNet baselines across accuracy, AUC, precision, recall, and F1-score.

3. A paired augmentation pipeline that applies identical spatial transformations to corresponding cover-stego images, preserving their structural correspondence during
training.

4. An ablation study using an SRM+SRNet configuration to quantify the contribution of fixed SRM preprocessing relative to the baseline SRNet architecture.

5. Grad-CAM visualizations identify which image regions the model weighted most heavily when making classification decisions.