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Restore JPG Photo Quality — Fix JPEG Compression and Damage

Restore JPG and JPEG photos that have been degraded by compression, repeated saving, social media re-encoding, or age. Our AI specifically targets JPEG artifacts — banding, blockiness, ringing — and reconstructs the clean detail underneath.

Free local tracing needs no account. AI tools use credits and upload files for processing.

Explore features and examples

From your image to editable paths

Choose the workflow that suits your file.
  1. 01

    Open your file

    PNG, JPG, WebP, AVIF, GIF, or BMP up to 10 MB in the free workspace (the AI converter takes PNG, JPG, WebP, or AVIF). Existing SVGs can be edited in the free workspace.

  2. 02

    Trace and inspect

    Preview the shapes and colors. Clear logos and flat artwork usually trace more predictably than photos.

  3. 03

    Make it yours

    Edit the SVG, compare optional optimization, and download your result.

Working with your SVG

May reduce visible scratches and stains

May reduce visible scratches and stains

In Your Browser

Upload a PNG, JPEG, or WebP file and download the result when processing finishes. Nothing to install.

Source-dependent color adjustment

Source-dependent color adjustment

No Watermark

Download the result without a watermark, then check it before you use it. Results depend on the source image.

JPG, PNG, and WebP input

JPG, PNG, and WebP input

Multi-Tool Platform

After processing, use our other AI tools — upscaling, restoration, vectorization — all in one platform with shared credits.

AI conversion features

  • Process JPG/JPEG files directly
  • May reduce visible scratches and stains
  • Source-dependent color adjustment
  • May enhance visible facial detail
  • Noise and grain reduction
  • JPG, PNG, and WebP input
  • No software installation required
  • Works in any modern browser
  • Commercial use allowed
  • Pay-per-use — no subscription
  • 1 free credit after you verify your email

Questions about your file

Free local tools. Optional AI credits.

Local tracing and SVG editing need no credits. AI conversion includes one credit after email verification; additional packs start at $9.99.

See AI pricing

The Five Types of JPEG Damage and How AI Fixes Each One

JPEG compression creates five distinct artifact types, each damaging your photos in a different way. Blocking artifacts appear as a visible 8x8 pixel grid, most obvious in smooth areas like sky or walls. Ringing artifacts (also called Gibbs phenomenon) create ghost echoes around sharp edges — look at dark text on a light background and you will see faint halos. Color bleeding occurs when the chroma subsampling (4:2:0) spreads color information across neighboring pixels, causing red from a shirt to leak into adjacent gray areas.

Mosquito noise shows up as flickering, buzzing artifacts around high-contrast edges — the name comes from the way these small distortions seem to "buzz" around object boundaries. Finally, banding (posterization) transforms smooth gradients into visible stair-stepped color bands, turning a beautiful sunset into a series of discrete color strips. Each of these artifacts has a different mathematical cause and requires a different correction strategy.

What makes AI restoration uniquely powerful for JPEG damage is generation loss — the accumulation of artifacts from repeatedly opening, editing, and re-saving a JPEG file. Each save cycle requantizes the DCT coefficients, compounding errors. A photo saved 5 times at quality 80 looks significantly worse than one saved once at quality 80. Social media makes this worse: you upload a photo to Instagram (re-compressed), someone screenshots it (re-encoded), shares to WhatsApp (re-compressed again), and by the time it reaches you, the image has been through 3-4 rounds of lossy encoding. Our AI can reverse much of this accumulated damage.

Pro Tips for Better Results

Identify your specific artifact types before restoring

Zoom to 200-400% and look at smooth areas (sky, walls, skin) for blocking and banding. Check around sharp edges (text, object boundaries) for ringing and mosquito noise. Look at color transitions for color bleeding. Knowing what is wrong helps you evaluate whether the restoration was successful.

Save the restored output as PNG to stop the damage cycle

After restoration, saving back to JPEG starts a new round of compression damage. Save as PNG (lossless) to permanently preserve the restored quality. You can always convert to JPEG later for web use, but keep the PNG as your master copy. This single step prevents future generation loss.

Process the oldest available version of the photo

If you have multiple copies of the same photo (in email, cloud storage, camera roll, social media), find the oldest or highest-quality version. Each copy may have gone through different compression pipelines. The version with the least generation loss will produce the best restoration results.

Compare skin tones before and after restoration

Skin is one of the hardest areas for JPEG — compression creates both banding across skin gradients and color bleeding from nearby objects. After restoration, zoom into faces and compare skin tone smoothness and color accuracy against a known reference. The AI should have smoothed banding while preserving natural skin texture variation.

Understanding JPEG Generation Loss and Why It Compounds

JPEG compression transforms image data using the Discrete Cosine Transform (DCT), then quantizes the frequency coefficients to reduce file size. This quantization is lossy — it permanently discards data. When you open a JPEG, it is decoded back to pixels, but the original pre-quantization values are gone. Re-saving performs a new DCT and quantization on already-degraded data, compounding errors. After N saves at quality Q, artifacts grow approximately as sqrt(N) times the single-save error. At quality 80, a single save produces mild artifacts. After 5 saves, artifacts are roughly 2.2x worse. After 10 saves, 3.2x worse. This is why photos shared through messaging apps degrade so quickly — each forwarding event is another save cycle. Our AI restoration model is trained on images with varying degrees of generation loss, from single-save to heavy multi-generation degradation, and adapts its correction intensity accordingly.

Common Mistakes to Avoid

Applying sharpening filters before JPEG artifact removal
Sharpening amplifies artifacts — it makes block boundaries more prominent and ringing halos more visible. Always remove artifacts first with our restoration tool, then apply sharpening only if needed afterward. In most cases, the AI restoration adds enough sharpness during the process that no additional sharpening is required.
Using noise reduction tools designed for camera sensor noise on JPEG artifacts
Camera sensor noise (grain) and JPEG compression artifacts are fundamentally different degradations. Noise reduction tools like Lightroom's denoise or Topaz DeNoise target random grain, while JPEG artifacts are structured patterns (block boundaries, ringing). Using the wrong tool can smear real detail while leaving structured artifacts untouched. Our JPEG restoration specifically targets compression artifacts.
Restoring a JPEG and then uploading the result to social media at low quality
Social media platforms re-compress all uploads, typically at quality 70-80. This can reintroduce mild artifacts into your freshly restored image. There is no way to avoid this re-compression, but you can minimize the impact by uploading at the platform's maximum accepted resolution, which gives the re-encoder more data to work with.