Higher resolution - Real-ESRGAN super-resolution

Increase image resolution up to 4x in one pass

Need more pixels without a mushy resize? PhotoSharpener raises width and height while reconstructing real texture, so exports look like they came from a higher-megapixel source—better for print specs, crop room, ecommerce zoom, and sharp fullscreen visuals.

Max output
Up to 4x
Avg. time
~8s
Formats
JPG - PNG - WebP
After enhancement
Before enhancement
Lower resolution
Higher resolution
Drag to compare the higher-resolution output
From low pixel count to usable size

Increase resolution with AI reconstruction

Upload a file or paste a URL. We run cleanup and super-resolution in one step, then you compare and download a higher-resolution image—no manual masking or filter stacks.

01

Upload your source image

JPG, PNG, or WebP. Phone shots, small web assets, scans, screenshots, and AI renders all work.

02

AI raises resolution and rebuilds detail

Real-ESRGAN outputs more pixels while sharpening edges and texture; portraits get automatic face-aware restoration.

03

Compare at full size, then export

Use the slider to verify the gain, then download a file with higher pixel dimensions for your workflow.

Raise Resolution in Seconds

Upload any image and get a higher-resolution version back with AI.

Drop your image here

or click to browse

More pixels, not just a bigger blur

True resolution gain, not interpolation alone

Stretching width and height with classic resampling adds pixels but rarely adds clarity. Super-resolution targets the missing high-frequency information so your larger canvas still reads sharp when you zoom, print, or crop.

  • Real-ESRGAN core

    Generative upscaling trained on real photos rebuilds texture that simple resize would smear.

  • Crisp edges at new dimensions

    Keeps lettering, product edges, and fine lines defined after the resolution bump.

  • Up to 4x pixel dimensions

    Turn a tight crop or thumbnail into headroom for banners, posters, or high-DPI exports.

Photo with increased resolution via AI super-resolution — after
Photo with increased resolution via AI super-resolution — before
Before
After
Portraits that stay believable

Faces keep natural texture at higher resolution

Boosting resolution on people is where cheap tools show plastic skin and glassy eyes. Face-aware processing keeps identity intact while lifting detail so headshots and family photos still look human at larger sizes.

  • Skin micro-contrast preserved

    Avoids over-smoothing when pixel count jumps.

  • Eyes and lashes stay sharp

    Critical portrait cues remain clear after enlargement.

  • Even quality in group shots

    Multiple faces get consistent treatment in one frame.

Portrait with higher resolution and natural skin detail — after
Portrait with higher resolution and natural skin detail — before
Before
After
Also included

Resolution boost plus full enhancement pass

Every run also applies sharpening, artifact cleanup, and optional face restoration so you are not chaining three separate apps after you increase resolution.

Try the full toolkit

AI photo sharpening

Add clarity after the resolution step without harsh halos.

Face restoration

Optional GFPGAN path for natural facial detail on difficult scans.

Noise and artifact cleanup

Reduces JPEG blocks and grain before they scale up with the new pixel grid.

Batch processing

Pro and Studio plans process whole folders in parallel with filenames preserved.

Resolution questions

Before you increase image resolution

Practical answers about pixel gain, limits, and when AI resolution increase helps most.

It means raising the pixel dimensions (width and height) of a raster image so you have more samples to work with. Done well—especially with AI super-resolution—the new pixels carry reconstructed detail instead of looking like a soft digital zoom.

PhotoSharpener increases resolution up to 4x the original resolution, which covers most print, crop, and display needs without unrealistic promises.

Often yes for mild blur, JPEG softness, and low-res sources. Severe motion blur or a completely missed focus point cannot be perfectly recovered, but a resolution pass plus reconstruction usually produces a more usable file than a plain upscale.

Traditional resampling guesses new pixels by averaging neighbors. Super-resolution models are trained to predict plausible high-frequency detail, which usually preserves edges and texture better when you need a real jump in pixel count.

Yes. Designers often increase image resolution first so the file meets minimum pixel dimensions for a print size or large-format display, then finish color in their usual tools.

JPG, JPEG, PNG, and WebP. Very large sources (around 24MP+) may require paid plans with extra GPU memory per job.

Yes. Files are transferred securely, processed, and automatically deleted after delivery. We do not train on your images or reuse them for marketing.

Ready when you are

Start from a small file. Export with more pixels and clearer detail.

Preview the resolution increase before you commit. Unlock full output when you are happy with the comparison.

See pricing ->
  • Images auto-deleted after processing
  • Most jobs finish in under 10s
  • Up to 4x from a single pass