DRIFT: Deep Restoration, ISP Fusion, and Tone-mapping
Smartphone cameras have gained immense popularity with the adoption of high-resolution and high-dynamic range imaging. As a result, high-performance camera Image Signal Processors (ISPs) are crucial in generating high-quality images for the end user while keeping computational costs low. In this paper, we propose DRIFT (Deep Restoration, ISP Fusion, and Tone-mapping): an efficient AI mobile camera pipeline that generates high quality RGB images from hand-held raw captures. The first stage of DRIFT is a Multi-Frame Processing (MFP) network that is trained using a adversarial perceptual loss to perform multi-frame alignment, denoising, demosaicing, and super-resolution. Then, the output of ...
| Authors | Soumendu Majee, Joshua Peter Ebenezer, Abhinau K. Venkataramanan et al. |
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| Primary category | eess.IV |
| Published | 3 April 2026 |
| Last updated at source | 12 April 2026 |
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