AI Video Upscaling & Enhancement: Improve Old & Low-Quality Foota

By Zgian Editorial

How to upscale, denoise, sharpen and restore video without destroying the original image—and how to build a practical enhancement pipeline for VFX, archives and AI-generated footage.

What is AI video upscaling?

Traditional upscaling enlarges an image by interpolating existing pixels. AI video enhancement can go further by using learned models to estimate detail, reduce noise, restore faces, improve focus or create intermediate frames.

The important word is estimate. AI cannot literally recover every detail that was never captured. It generates the most plausible reconstruction the model can infer from the available information.

1. Start with the source, not the output resolution

Before choosing an AI model, inspect what is actually wrong with the footage. A 1080p clean image may need only a resolution increase. A damaged SD archive may need deinterlacing, denoising, deblocking, stabilization and restoration before scaling.

Topaz’s current enhancement controls distinguish progressive and interlaced source types and provide different AI models for enhancement, denoising and upscaling.

2. The professional AI restoration workflow

1. Preserve the original. Never overwrite the source.
2. Inspect the clip. Identify noise, blur, compression, interlacing and frame-rate issues.
3. Test a short section. Compare several models before processing the entire film.
4. Restore first. Remove serious degradation before adding aggressive detail.
5. Upscale. Choose the smallest enlargement that meets delivery requirements.
6. Check temporal consistency. Watch for flicker, crawling texture and changing facial detail.
7. Finish. Grade, add controlled grain and export the final master.

3. 2x, 4K and higher upscaling

There is no universal rule that 4K always looks better. A smaller, carefully processed output can look more natural than a heavily reconstructed image.

Topaz currently advertises high-accuracy enhancement up to 4K across live-action, generative AI and animation content, and its Video AI Pro product advertises outputs up to 24K. These are product capabilities, not a guarantee that every source will look good at those sizes.

4. AI denoising

Noise reduction is often more important than sharpening. If you sharpen noisy footage first, you may amplify the noise and compression artifacts.

Topaz currently lists dedicated denoising models and describes its models as being trained to distinguish noise from detail.

5. Sharpening and detail recovery

Sharpening should improve perceived detail without creating halos, ringing or plastic-looking skin. AI enhancement is particularly sensitive to faces, text and repeating textures.

• Inspect eyes and hair at 100%.
• Check skin for waxy textures.
• Check straight edges for halos.
• Check patterned clothing for invented detail.
• Compare the enhanced image against the original, not only the final output.

6. Restoring old and archival footage

Old footage can contain multiple problems at once: low resolution, film grain, scratches, interlacing, compression, faded contrast and unstable frames. Treat restoration as a pipeline rather than applying one “enhance” button.

Topaz currently positions Video for recovering and upscaling old archival video, while Project Starlight is a research-derived diffusion enhancement system designed for degraded, low-resolution video and temporal consistency.

A safer archive workflow

7. Enhancing AI-generated video

AI-generated footage has a different problem: it may already be sharp enough in resolution but lack fine texture, stable faces, natural detail or consistent edges. Upscaling should therefore be used as a finishing step, not as a substitute for fixing a bad generation.

Topaz currently markets its creative video upscaling specifically for generative AI footage as well as traditional footage, with precise and creative enhancement modes.

8. Topaz Video vs DaVinci Resolve

Topaz’s own 2026 comparison describes Topaz Video as a dedicated enhancement tool and Resolve as the broader editing, grading, VFX and audio environment. Topaz also currently provides plugins for After Effects and DaVinci Resolve Studio.

9. A practical Zgian workflow for a low-quality clip

1. Import the original clip.
2. Identify whether it is progressive or interlaced.
3. Remove obvious noise or compression before heavy sharpening.
4. Test two or three AI models on a short representative section.
5. Compare faces, hair, text and high-frequency textures.
6. Choose the least artificial-looking result.
7. Upscale to the delivery resolution.
8. Bring the result into your NLE/compositor.
9. Perform final color and VFX work.
10. Add restrained grain if the image has become too synthetic.

10. Common AI upscaling mistakes

11. Final QC checklist

1. Compare original and enhanced footage at 100%.
2. Watch faces throughout the clip.
3. Check hair and fine texture.
4. Look for temporal flicker.
5. Check text and logos.
6. Inspect repeated patterns.
7. Check motion blur.
8. Check color consistency.
9. Check that the enhancement has not changed important creative details.
10. Review the final master at normal playback speed.

How this fits the Zgian AI Video cluster

Frequently asked questions