Deep Phi · The structure engine

Discover the hidden structure of information.

phiXplorer reveals the structure inside any image — textures, edges, the fabric a scene is made of — guided by φ, Deep Phi’s proprietary structural measure. Deterministic. Featherweight. Nothing invented.

Try phiXplorer How it works

A nebula and its φ structural map — Input → φ structural mapEven the cosmos has structure. Image: NASA/ESA, Hubble — public domain.

φImagesφSuper-ResolutionφEnhancementφVideoφCompressionφComputer VisionφScientific ImagingφSignalφImagesφSuper-ResolutionφEnhancementφVideoφCompressionφComputer VisionφScientific ImagingφSignal

0.2–0.8M

parameters — featherweight

Deterministic

same input, same output

100%

on-device — zero servers

invented pixels

What is φ

A measure of structure — not a model

φ scores, at every point of an image, how rich the local structure is — independent of meaning. The formula stays inside Deep Phi; only its behaviour ships in the model.

Input

Any image, exactly as it is — no labels, no priors, no setup.

φ map

Hot where structure lives — textures, edges, micro-patterns. Dark where it’s flat.

Structure-aware result

Models spend their effort exactly where φ points, and nowhere else.

Image and its φ map — Feathers, beak and eye light up; the blurred background stays ignored.

Same pixels in, same map out — no randomness, nothing hallucinated. φ is a deterministic measure you can audit, not a generative model you have to trust.

Explore the technology →

Deterministic by nature

φ, seen as a relief of structure

Read an image as a landscape: peaks where structure is dense — feathers, edges, texture — plains where it is flat. The very same pixels always produce the very same surface. A measurement, drawn to the pixel.

The image as a structural landscape — peaks are rich zones, plains are flat areas.

The same values as isolines — a topographic map of structure, traced to the pixel.

Why φ

The right tool, at the right size

Deterministic

Same input, same output. Reproducible and auditable — the opposite of a generative guess.

Featherweight

0.2–0.8M parameters. Runs on-device, inside a browser — no datacenter, no GPU farm.

Transparent

φ’s output is a picture you can look at. You literally see what the model sees.

Multi-domain

One structural prior, many pipelines: super-resolution, enhancement, compression and beyond.

Applications

One structural prior, many pipelines

What ships today, what’s in research, and where φ is heading.

Super-Resolution ×2

● Live

Upscale images and video, structure-first, no invented detail.

φ Enhancement

● Live

Contrast and sharpness placed exactly where φ sees structure.

Denoising

● Live

Removes sensor noise and grain while φ preserves real detail — a small model that keeps structure sharp.

Gradient removal

● Live

Astrophotography: φ lifts the light-pollution and vignetting gradient while preserving stars and nebulosity.

Video ×2

● Live

Frame-by-frame upscaling, encoded to MP4 in your browser.

See all applications →

Zoom ×8

On requestDrag to compare

Real low-resolution details, enlarged ×8 — no downscale, nothing hallucinated. A capability preview: run offline, not in the ×2 studio.

Macaw — eye & feathers
A real detail enlarged ×8 — plumage and eye rebuilt from the pixels that exist.

Tiny text
Letters become legible again — not a single character invented.

Moon — craters
Crater rims recovered from a small, real crop.

Jupiter — cloud bands
Banding and the storm regain their edge.

Lighthouse — stonework
Masonry sharpens; the smooth sky stays clean.

Foliage — branches
Branch edges and veins reconstructed.

×8 model — 4.66 MB, φ inside. Runs offline on your own hardware; available on request.

Denoising — real sensor noise

On requestDrag to compare

Real camera pairs: the same scene shot at base ISO and at ISO 6400. No synthetic noise — this is what the sensor actually produced. The in-browser studio runs the synthetic-noise model; this is the one trained on real noise. Hover for the pixel loupe.

Bronze, ISO 6400
Real sensor noise, not simulated. The chroma blotches go; the pitting and patina of the metal stay.

Carved drapery, ISO 6400
Grain lifted from the stone while every chisel mark and fold survives.

Sculpted shell, ISO 6400
Colour speckle cleared from the shadows; the carved edges keep their bite.

Lobster shell, ISO 6400
Chroma noise is worst on saturated reds — cleared here without smearing the shell.

Stone detail, ISO 6400
A harder case: fine relief, where the model stays deliberately cautious.

Claw, ISO 6400
Wet highlights and speckled shell — texture kept, grain gone.

Real-noise model — 0.71 MB, φ inside: the same size as the one running in the studio, but trained on genuine camera pairs instead of synthetic noise. +3.4 dB over the in-browser model on real photographs, up to +7.7 dB on the noisiest. Runs offline on your own hardware; available on request.

Source pairs: NIND — Natural Image Noise Dataset, by Trougnouf (Benoit Brummer) — CC BY 4.0.

Open the live studio Runs entirely in your browser — nothing uploaded.

Roadmap

From a measure to a platform

2025

Foundations

φ core, dense structural maps, on-device inference.

2026

phiXplorer

The web studio — super-resolution, enhancement, video. This site.

2027

Deep Phi platform

Specialised models per domain, batch tooling, quality metrics.

SDK & Cloud API

φ-guided processing as a building block for your own products.