L1 ⚛ L1-102 ⊙ Testnet

Hyperspectral Imaging (pushbroom / AVIRIS-style)

Remote Sensing · Airborne/satellite hyperspectral

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⬇ L1-102.md

# ⚛ L1 Principle — Hyperspectral Imaging (pushbroom / AVIRIS-style) **ID:** `L1-102` · **Status:** ⊙ Testnet (genesis catalog) > **🌐 Domain:** Remote Sensing — *Airborne/satellite hyperspectral* > **🎯 Problem class:** linear inverse · **🧮 Solution space:** 3D spectral image > **📡 Carrier:** photon · **🌫 Noise:** gaussian > **⚖ Difficulty (δ):** 3 · **⛓ Block:** 41554197 --- ## 🧠 1. Introduction **Hyperspectral Imaging (pushbroom / AVIRIS-style)** is a **linear inverse problem** whose unknown lives in **3D spectral image** space, within the **Airborne/satellite hyperspectral** sub-domain of **Remote Sensing**. Measurements consist of photons collected by an optical detector via a **pushbroom spectrograph** sensing mechanism. The forward operator applies, in order: L · spectral disperse operator; S · scan · pushbroom operator; pixel-level spatial averaging on the detector. Observations are corrupted by additive Gaussian noise. Existence of the recovered 3D spectral image is guaranteed within the declared Omega bounds. Uniqueness holds on the measurement-supported subspace; out-of-support modes are controlled by the declared priors. Stability is moderately conditioned (kappa_eff ~= 10); atmospheric_water_vapor dominates the stability cliff; smile_distortion and the remaining mismatch parameters contribute higher-order bias terms. Additive gaussian thermal/electronic noise sets the irreducible data-fidelity floor, while mild Tikhonov or analytic inversion is sufficient at the nominal Omega point. ## ⚙ 2. Forward Model Physical chain: **x** → L · spectral disperse → S · scan · pushbroom → Spatial integration → **y** (detector). ``` y = ∫_A dA `S.scan.pushbroom` `L.spectral_disperse` x + n, n ~ 𝒩(0, σ²) ``` **Measurement DAG:** | Primitive | What it does | |---|---| | `L.spectral_disperse` | L · spectral disperse operator | | `S.scan.pushbroom` | S · scan · pushbroom operator | | `int.spatial` | Pixel-level spatial averaging on the detector | ## 🔬 3. Physics Fingerprint | Property | Value | |---|---| | Domain | Remote Sensing | | Sub domain | Airborne/satellite hyperspectral | | Carrier | photon | | Problem class | linear_inverse | | Solution space | 3D_spectral_image | | Noise model | gaussian | | Integration axis | spatial | | Difficulty delta | 3 | | L dag | 3 | ## 📡 4. Measurement Model Existence of the recovered 3D spectral image is guaranteed within the declared Omega bounds. Uniqueness holds on the measurement-supported subspace; out-of-support modes are controlled by the declared priors. Stability is moderately conditioned (kappa_eff ~= 10); atmospheric_water_vapor dominates the stability cliff; smile_distortion and the remaining mismatch parameters contribute higher-order bias terms. Additive gaussian thermal/electronic noise sets the irreducible data-fidelity floor, while mild Tikhonov or analytic inversion is sufficient at the nominal Omega point. | Metric | Value | |---|---| | Metric | PSNR_dB | | Secondary | SSIM | ## 📏 5. Operating Range (Ω) **Center problem class:** `hyperspectral_pushbroom` · **Forward operator:** `hyperspectral_pushbroom_forward` **Center point:** | Parameter | Unit | Value | |---|---|---| | H | px | 512 | | W | px | 640 | | Gsd m | m | 30 | | Snr db | dB | 35 | | N bands | bands | 224 | | Lambda range nm | nm | 400 – 2500 | | Smile distortion | — | 0 | | Atmospheric water vapor | — | 0 | **Allowed bounds:** | Parameter | Unit | Range | |---|---|---| | H | px | 128 – 8192 | | W | px | 128 – 8192 | | Gsd m | m | 1 – 1000 | | Snr db | dB | 10.0 – 45.0 | | N bands | bands | 32 – 500 | | Spectral mixing | — | 0.0 – 0.3 | | Smile distortion | — | 0.0 – 0.1 | | Atmospheric water vapor | — | 0.0 – 0.3 | ## 🎯 6. Tolerance (ε) **Center tolerance:** 30.0 | Metric | Range | |---|---| | Psnr db | 5.0 – 40.0 | ## ⚖ 7. Hardness Function Hardness scales as **`epsilon_fn`** on **PSNR_dB**, with κ = `200` and δ = `3`. ## 💾 8. Reference Dataset - **primary** · weight 1.0 · IPFS _(not pinned yet)_ ## 9. On-chain Registration - **Chain hash:** `0x1de25a8d6b901ac0860789aa40ac61410173d64a652c9614b33e62395cf43ce3` - **Chain tx hash:** `0x4d41e8f4d7563e8275ef9f936b4857f4603f3960bd4c7dccbff8c06e65848dcf` - **Chain block:** `41554197` --- ## File Mapping This bundle consists of: `L1-102.md`, `L1-102.json`. | File | Role | How to regenerate | |------|------|-------------------| | `L1-102.md` | Source of truth — edit this | Human or LLM | | `L1-102.json` | Structured metadata for the registry | LLM regenerates from the sections above | **Prompt for your LLM after editing this Markdown:** > Read the attached Markdown. Regenerate the sibling `.json` so every field matches. > Preserve the schema documented in the rows above. > Output each file in its own fenced code block tagged with the filename. > Output only the JSON object. _This Markdown was auto-synthesized from the catalog row for `L1-102`._ _Edit it, regenerate the JSON, and submit at [/submit](/submit) to claim the artifact._

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Read the attached Markdown (L1-102.md).
Regenerate L1-102.json so every field matches the Markdown.
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L2-102-001 Hyperspectral Imaging (pushbroom / AVIRIS-style) Mismatch-Only Spec

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📋 JSON metadata

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  "chain_block": 41554197,
  "chain_hash": "0x1de25a8d6b901ac0860789aa40ac61410173d64a652c9614b33e62395cf43ce3",
  "chain_tx_hash": "0x4d41e8f4d7563e8275ef9f936b4857f4603f3960bd4c7dccbff8c06e65848dcf",
  "domain": "Remote Sensing",
  "hardness_fn": {
    "delta": 3,
    "kappa": 200,
    "metric": "PSNR_dB",
    "type": "epsilon_fn"
  },
  "initiator_dataset": [
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      "license_hash": null,
      "name": "primary",
      "weight": 1.0
    }
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  "layer": "L1",
  "observable_profile": {
    "metric": "PSNR_dB",
    "regime": "Existence of the recovered 3D spectral image is guaranteed within the declared Omega bounds. Uniqueness holds on the measurement-supported subspace; out-of-support modes are controlled by the declared priors. Stability is moderately conditioned (kappa_eff ~= 10); atmospheric_water_vapor dominates the stability cliff; smile_distortion and the remaining mismatch parameters contribute higher-order bias terms. Additive gaussian thermal/electronic noise sets the irreducible data-fidelity floor, while mild Tikhonov or analytic inversion is sufficient at the nominal Omega point.",
    "secondary": "SSIM"
  },
  "physics_fingerprint": {
    "L_DAG": 3.0,
    "carrier": "photon",
    "difficulty_delta": 3,
    "domain": "Remote Sensing",
    "integration_axis": "spatial",
    "noise_model": "gaussian",
    "primitives": [
      "L.spectral_disperse",
      "S.scan.pushbroom",
      "int.spatial"
    ],
    "problem_class": "linear_inverse",
    "sensing_mechanism": "pushbroom_spectrograph",
    "solution_space": "3D_spectral_image",
    "sub_domain": "Airborne/satellite hyperspectral",
    "title": "Hyperspectral Imaging (pushbroom / AVIRIS-style)"
  },
  "size_tiers": {
    "allowed_forward_operators": [
      "hyperspectral_pushbroom_forward"
    ],
    "allowed_omega_dimensions": [
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      "W",
      "N_bands",
      "lambda_range_nm",
      "GSD_m",
      "SNR_dB",
      "atmospheric_water_vapor",
      "smile_distortion",
      "atmospheric_water_vapor",
      "smile_distortion",
      "spectral_mixing"
    ],
    "allowed_problem_classes": [
      "hyperspectral_pushbroom"
    ],
    "center_spec": {
      "epsilon_fn_center": "30.0",
      "forward_operator": "hyperspectral_pushbroom_forward",
      "input_format": "measurement_only",
      "omega": {
        "GSD_m": 30,
        "H": 512,
        "N_bands": 224,
        "SNR_dB": 35.0,
        "W": 640,
        "atmospheric_water_vapor": 0.0,
        "lambda_range_nm": [
          400,
          2500
        ],
        "smile_distortion": 0.0
      },
      "problem_class": "hyperspectral_pushbroom"
    },
    "epsilon_bounds": {
      "psnr_db": [
        5.0,
        40.0
      ]
    },
    "omega_bounds": {
      "GSD_m": [
        1,
        1000
      ],
      "H": [
        128,
        8192
      ],
      "N_bands": [
        32,
        500
      ],
      "SNR_dB": [
        10.0,
        45.0
      ],
      "W": [
        128,
        8192
      ],
      "atmospheric_water_vapor": [
        0.0,
        0.3
      ],
      "smile_distortion": [
        0.0,
        0.1
      ],
      "spectral_mixing": [
        0.0,
        0.3
      ]
    }
  },
  "staked_pwm": 0.0,
  "status": "testnet",
  "sub_domain": "Airborne/satellite hyperspectral",
  "title": "Hyperspectral Imaging (pushbroom / AVIRIS-style)"
}

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