Image Enhance

Clean up and enlarge a selected image without leaving the canvas.

Choose the task

Open the image enhancement command for a selected image and choose the operation that matches the source problem. Auto / Recommended runs a quick local analysis (noise, blur, compression, resolution) and suggests a task with a confidence number — you can always override it.

Denoise reduces sensor noise and grain using a task-specific local denoising model.
Deblur reduces motion and defocus blur with a validated NAFNet checkpoint. Restoration is bounded: the model runs on a cropped preview first, and full-resolution work tiles adaptively so memory stays within budget.
Upscale enlarges with CPU, pixel-art, or the available local AI super-resolution path.
Restore + Upscale (and Deblur + Upscale) compose restoration before enlargement so noise or blur is not simply made larger.

Review before applying

The dialog previews a bounded representative crop and provides a draggable before/after comparison. Use the preview at a useful zoom for text, logos, thin lines, transparency, and edge transitions. A preview is not a full-resolution final result.

Output behavior

New layer is the default and preserves the source. Replace source commits the derived pixels atomically and remains undoable. Use the output options only when their semantics suit the document; enhancement results are materialized pixels and do not silently become re-editable model operations.

Honest capabilities

JPEG artifact removal is not offered as an operation: no model has passed Varve's design-content quality corpus for that task (denoising models smear 1px lines and UI text, and the JPEG-trained candidates were rejected on provenance or shape safety). Varve does not relabel a denoiser as a compression-restoration model, and it does not substitute an unrelated fallback when a requested task cannot run. Model quality and conversion evidence are published in the benchmark report.