Feature

Upscale

Alpha Real-ESRGAN upscaling: 8192×4096 native, up to 16384×8192

Included with every license

Alpha: Real-ESRGAN and Projection-Aware Upscale are available for testing and feedback. Their workflow can change before production release.

Upscale uses Real-ESRGAN, an AI upscaling model, to enhance your panoramas while accounting for the equirectangular projection. On an open render, click Resize and choose a target in its Upscale section. Transform 4K images into rich 8K or 16K outputs, up to the 16384×8192 application cap.

Resolution Scaling

4K

4096×2048

8 Megapixels

8K

8192×4096

33 Megapixels

16K

16384×8192

134 Megapixels

Key Features

Neural Upscaling

Real-ESRGAN uses deep learning to intelligently upscale images, adding convincing detail and texture rather than simple interpolation blur.

Detail Enhancement

Enhance textures, sharpen edges, and recover fine details lost during compression or lower-resolution rendering.

How Projection-Aware Upscale Works

One sphere, two projection regions

A flat-image upscaler treats every row alike even though equirectangular pixels stretch toward the poles. Projection-Aware Upscale keeps the mid-latitudes horizontally wrap-aware, processes north and south through stereographic polar caps, then blends the regions into one equirectangular result.

  • 1

    Wrap-aware mid-latitudes

    The panorama's left and right edges remain one continuous join

  • 2

    North polar cap

    The zenith is processed through a stereographic cap

  • 3

    South polar cap

    The nadir receives the same projection-aware treatment

  • 4

    Smooth recombination

    The cap bands blend back into the wrap-aware full frame

Use cases

Skyboxes

For your virtual world

VR Experiences

High resolution for virtual reality immersion

Concept Art

Develop rich high resolution worlds and consistent worlds for your IP project development

Vibe Coding

Use Hextile to agentically generate worlds for your vibe coded video game

Pipeline Integration

Upscale fits into your workflow as the final step after AI diffusion processing, or apply it directly to an existing panorama. Open the result and use Resize → Upscale; use Resize's Size section instead when the delivery needs an absolute dimension.

Apply after SDXL or SD3.5 processing
Upscale existing panorama libraries
Export at your target resolution
4K Input
Real-ESRGAN
16K Output

Technical Specifications

Model Real-ESRGAN (NCNN implementation)
Scale Factors 2× / 4× / 8× / 16× targets, up to the 16K edge cap
Input Formats PNG, JPEG, TIFF, EXR
Output Formats PNG (16-bit), JPEG, TIFF
Max Output Resolution 8192×4096 native, up to 16384×8192 with Real-ESRGAN upscaling
GPU Acceleration NVIDIA CUDA / Vulkan
VRAM Usage ~2-4 GB (tile-based processing)
Availability All licenses

Work on your own GPU

One-time licence from $360. No subscription, no per-render cloud charge.

30-day money-back guarantee on every purchase.

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