noritsu — C-41 negative processing in the Noritsu "look"

A CLI that inverts C-41 color negative scans in density space — the way Noritsu LS-600 and Frontier minilab scanners do — and renders a positive with a Noritsu-flavored tone curve and color correction. Built from a reverse-engineering study of the actual Noritsu LS-600 / EZ Controller 6.5 software (no scanner required).

python -m noritsu.cli scan_of_negative.tif -o positive.tif

Why this exists

The Noritsu LS-600 is a professional film minilab scanner whose output has a beloved, distinctive "look". People chase it with presets and plug-ins. This project goes one level deeper: it reads the actual ImgDataProc ("RD5X") engine binaries and correction tables from the LS-600 software stack, recovers the physics and the tone curves, then reimplements the conversion as a small, inspectable Python tool.

The inversion principle (confirmed from the engine):

A scanner measures transmittance. A color negative's dyes are complementary (C/M/Y) under an orange mask. Convert to density D = −log10(transmittance), remove the per-channel mask (Dmin), and normalize by the density range. Density conversion inherently resolves both the tonal and the complementary-color inversion in one physically-correct step.

Install

Requires Python 3.10+, numpy, Pillow, and tifffile (for 16-bit TIFF):

pip install numpy pillow tifffile

Usage

python -m noritsu.cli scan_of_negative.tif -o positive.tif

Point the input at a directory instead of a file and every image inside is batch-processed into the -o directory:

python -m noritsu.cli ./negatives/ -o ./positives/

The options you actually reach for

Option	Meaning
--srgb-input	your scan is sRGB-encoded (DSLR JPEG/flatbed): linearize it first
--stock portra160	use a per-stock profile fitted from real LS-600 pairs
--lab	gentler, print-ready rendering (see Lab mode)
--contrast 1.08	tone-curve contrast
--gamma 0.8	midtone gamma — lower lifts a thin negative
--preview	also write an 8-bit JPEG beside the output for a quick look

Full option reference

Input and output

Option	Default	Meaning
input	required	negative image, or a directory to batch-process
-o, --output	required	output positive, or output directory in batch mode
--bits 8|16	16	output bit depth
--preview	off	also write an 8-bit JPEG preview beside the output
--srgb-input	off	input is sRGB gamma-encoded; linearize before inverting
--black 0.02	0.0	scanner black level to subtract (0..1)
--no-crop	off	keep the clear margins instead of auto-cropping to the film area

Inversion — finding the orange mask and the density range

Option	Default	Meaning
--dmin R G B	auto	override film-base density (the mask) per channel
--dmax R G B	auto	override maximum density per channel
--dmin-pct	0.5	percentile used for auto Dmin
--dmax-pct	99.8	percentile used for auto Dmax — drop to 98.0 for a thin negative
--no-border	off	ignore the film rebate when estimating Dmin; use the percentile instead

Render — tone and color

Option	Default	Meaning
--contrast	1.05	tone-curve contrast
--gamma	0.98	midtone gamma (lower is brighter on a thin negative)
--toe	0.02	shadow lift
--sat, --saturation	1.0	saturation multiplier
--wb R,G,B	auto	manual white-balance gains
--no-auto-wb	off	disable automatic white balance
--real-curve	off	use the real Noritsu tone curve from CommonCalcPara.Dat (experimental; best with linear input)
--calib FILE.npz	none	fit to your own reference render (see noritsu/calibrate.py)
--stock NAME	none	per-stock profile: portra160, portra400, superia800
--lab	off	lab-tech rendering; implies --real-curve

Getting the best result

• Feed it linear data. The inversion assumes pixel value ∝ transmittance. If you shot the negative with a DSLR, develop the RAW linearly (no profile, no gamma). If you have a flatbed/JPEG scan, pass --srgb-input.
• Include the film border (or unexposed rebate) so Dmin can be estimated, or pass --dmin manually.
• Start with defaults, then tune --contrast and --sat.

Pipeline

1. linearize input (optional sRGB EOTF)
2. transmittance → density, per channel
3. estimate/remove Dmin (orange mask), normalize by Dmax − Dmin
4. auto white balance (neutralize residual cast)
5. Noritsu-style tone curve (control-point S-curve, per channel)
6. saturation adjustment
7. write 16-bit positive

Fidelity — how close to a real LS-600?

The inversion math is validated by a round-trip test (test_roundtrip.py, ~0.4% mean error). The tone curve and color stages are a faithful approximation of the Noritsu rendering, recovered from the engine's CommonCalcPara tone-curve tables and SpecialPcb per-film tables.

Validated against a real LS-600 (2026): an LS-600 owner provided raw scan frames (FULL*.RAW, headerless 3×uint16 BGR, 12-bit, 4042×6391), the machine's own processed 16-bit positives, and the real per-frame Correction Files (.prm, 0x504E8 bytes). That confirmed the recovered CF format field-for-field (checksum = signed-byte sum of the tail at u32[0], size, CorrParamHead=5, NKC-ICCS magic, SrcImg path), and the exact geometric crop+resample (UsImRct from TrzCorFile → align_to_machine()).

After calibration, this is how close our pipeline gets to the machine's own output (per-pixel normalized cross-correlation on 27 frames across 3 stocks):

Stock	ICE	Frames	Mean NCC	Min NCC	Mean RMS(/255)
Portra 400	off	3	0.940	0.926	27.6
Portra 160	on	6	0.936	0.904	27.5
Superia 800	off	12	0.881	0.838	40.7

The Portra numbers are tight — ~94% pixel correlation. Superia 800 is lower because the LS-600 internally uses per-film adjustments (its SpecialPcb tables) for different emulsions that our generic curve doesn't include. The per-stock calibration profile helps, but the actual SpecialPcb tables would close the rest.

Visually, the output is excellent on all stocks — "oh fuck yeah these are so good" (actual user quote). The gap is academic: per-frame density estimation variation plus missing per-film tables. It does not affect the practical result.

Per-stock calibration profiles

The repo ships per-stock profiles fitted from real LS-600 raw/TIFF pairs:

python -m noritsu.cli scan.tif -o out.tif --stock portra160
python -m noritsu.cli scan.tif -o out.tif --stock portra400
python -m noritsu.cli scan.tif -o out.tif --stock superia800

These absorb the scanner's per-unit spectral response and the film stock's dye characteristics. The generic pipeline (no --stock) also works well for any C-41 film.

Lab mode

A real LS-600 operator told us they dial contrast -2, highlights -2, shadows -2, sharpness 3-5, and auto contrast 5 on every scan because the defaults are too contrasty. --lab applies those same corrections:

python -m noritsu.cli scan.tif -o out.tif --lab

Equivalent to: --contrast 0.90 --gamma 0.90 --toe 0.04 --sat 0.95 --real-curve. A gentler, more print-ready rendering.

ICE was not the culprit

We previously thought the remaining gap was ICE/dust masking, but the owner sent frames with ICE disabled and the NCC was the same. The residual is consistent regardless of ICE state. The real gap is per-film spectral response and the missing SpecialPcb per-film tables.

LS-600 raw scan input

noritsu/ls600raw.py decodes the scanner's FULL*.RAW frames (headerless 3×uint16 LE BGR, 12-bit data, 6391×4042):

from noritsu.ls600raw import load_ls600_raw
arr = load_ls600_raw("FULL000000010000.RAW")   # float32 (6391,4042,3) BGR [0,1]

The CLI reads them directly — python -m noritsu.cli FULL000000010000.RAW -o out.tif — and batch mode picks up .RAW files alongside TIFFs. The format carries no header, so dimensions are recovered from the byte count: exact match against known frames first, then known-axis division (a 4042-wide frame of any length), then a unique-factorization fallback; a file whose size is ambiguous is refused rather than guessed. The 12-bit container is sensed from the data, so a hypothetical 16-bit dump won't be blown out 16×. Sizes/order were recovered from real LS-600 frames and verified against the machine's own outputs (and independently agree with the loader in NegPy PR #765).

Coolscan scanner NEFs are also detected structurally (RGB SubIFD, no Bayer mosaic) and read via tifffile without a rawpy demosaic pass, which would otherwise mangle them; camera NEFs still go to rawpy.

See samples/compare.jpg for a side-by-side.

Documentation

• docs/JOURNEY.md — the full chronological story of the reverse-engineering work: unpacking the installers, mapping the pipeline, decoding the .dat tables, the density inversion, driving the real engine headless, and the CF-format / validation-gate work.
• docs/BLOG_POST.md — a tighter, written-up version of the same story, and how this differs from preset-based "Noritsu look" tools.
• docs/RD5X_INPUT_FORMATS.md — the recovered film raster ABIs.
• docs/RD5X_XML_SCHEMA.md — the engine's XML command schema.

How this differs from a preset

Negative Lab Pro and similar tools ship a tuned approximation of the look (Lightroom grading tweaks over a proprietary camera profile). This project's model is reconstructed from the actual shipped Noritsu assets — the SpecialPcb per-film gamma/contrast/white-balance tables, the CommonCalcPara tone curve, and the engine's density-domain pipeline. It is physically grounded, inspectable (open a table and see the curve), and calibratable to any reference render. It does not claim byte-identical LS-600 output (your scanner's spectral response and a unit's per-unit calibration differ).

License

MIT. The reverse-engineering was done from public installer binaries for research/compatibility purposes; no Noritsu source code, firmware, or vendor binaries are distributed here — only the format knowledge recovered from them and this original implementation.

Coolscan → Noritsu workflow (2026-08-04)

This pipeline works with any scanner's linear C-41 raw, not just the LS-600. The density inversion is scanner-agnostic — the math doesn't care which CCD captured the transmittance.

From Scan Studio archive

Scan Studio exports full-res linear TIFFs in its Archive/ folder:

python -m noritsu.cli ScanStudio1.tif -o noritsu_render.tif \
  --gamma 0.8 --contrast 1.15 --sat 1.2 --dmax-pct 98.0 --preview

Tuning for your negative

The defaults assume a normally-dense C-41 negative. If your frame looks underexposed (thin negative), the pipeline compensates:

Negative	--dmax-pct	--gamma	Result
Normal/dense	99.5–99.8	0.9–1.0	Standard Noritsu
Thin/underexposed	98.0	0.7–0.8	Lifted, open shadows
Overexposed/dense	99.9	1.0–1.1	Rich, punchy

Key insight: gamma > 1 on a low-contrast positive makes things darker. For a thin negative, lower gamma (0.7–0.8) lifts the image to proper exposure. Add --contrast 1.05–1.15 to restore snap.

The real LS-600 calibration (--calib) does not transfer to other scanners — it encodes the LS-600's specific CCD spectral response. The generic pipeline is the correct approach for cross-scanner use.

Validated

A real LS-600 owner's raw frames plus a Coolscan 5000 full-res archive both produce beautiful Noritsu-style positives through this pipeline.