Compression & memory · Research & Algorithms

A real CT scan tests our compression idea

A real measurement operator and a strong raw-data control changed the answer. Our compact spline messages were not the best way to preserve this scan.

INSIDE THE EXPERIMENT

One scan. Different ways to remember it.

Drag the divider to inspect the reconstructions from the same measured acquisitions.

Walnut slice reconstructed from eight-bit raw measurements with total variation Same walnut slice reconstructed from cardinal-spline statistics Cardinal splineRaw + TV

MEASURED FAN-BEAM CT · 2D

What survives compression?

The shell, internal folds and reconstruction artifacts are data—not a drawing of a scanner.

Cardinal spline
6.31% view error 14,100 message bytes
Eight-bit raw + TV
4.23% view error 7,608 message bytes

Errors predict development projections, not image ground truth. Numeric message sizes exclude shared infrastructure.

50% compact / 50% raw
Actual archived 82 × 82 reconstructions, shown at their native information resolution with the same linear grayscale window; no AI enhancement. Images are from the original admission comparison, not the later matched-TV diagnostic. The slice is not a 3D volume or a patient scan. Data: Hämäläinen et al., Tomographic X-ray data of a walnut, CC BY 4.0. Reconstruction and display: this project. No reserved measurements were read for this figure.

Follow the information

From input to outcome

The arms encode the same measured specimen with different representations; they are alternatives, not layers of one codec. A shared scanner matrix is needed to interpret messages and predict the held measured views.

Scroll the diagram horizontally to follow the route. Keyboard: focus the diagram, then use the arrow keys.

Measured walnut views → Encode each donor → Actual message budget → Recipient reconstruction → Held-view prediction. The arms encode the same measured specimen with different representations; they are alternatives, not layers of one codec. A shared scanner matrix is needed to interpret messages and predict the held measured views.
Information-flow map. One specimen; reserved views stay unscored. Raw 8-bit + TV beats the tested proposal. Original vector schematic based on the method and evidence discussed in this article; signal shapes and icons are illustrative, not additional measurements. Open full-size diagram ↗

Read the main route from left to right; labelled side branches show additional inputs, checks or feedback. The sections below explain the operations and their experimental limits.

Start from measured projections

The experiment uses a public walnut CT slice and its supplied fan-beam matrix, not targets generated by the same spline basis we later fit. Three simulated donors each receive thirty views. Fifteen additional views select regularization, and fifteen remain unscored. The task is prediction of held measured views on one specimen—not diagnosis or ground-truth image reconstruction.

Follow the bytes, not only the image

Each simulated donor receives thirty measured projection views. Its compact message is decoded with a shared scanner matrix and represented image basis. The recipient then chooses a reconstruction prior and predicts held measured views. The attractive image is an output of this whole pipeline, not a ground-truth label against which the method was trained.

A fair resource comparison includes the shared operator separately from per-scan transmission. The tiny messages rely on megabytes of retained operators and normals. Raw eight-bit measurements use a different tradeoff: more direct observation access and an ordinary TV reconstruction. That control is both smaller and more accurate than the two larger cardinal messages.

What crosses the measurement boundary?
What crosses the measurement boundary?. Original scientific diagram; the stated component and information flow, not an additional experiment. Open full-size figure ↗

Give the simpler alternatives a fair chance

Cardinal and cosine spaces have exactly the same dimensions and numeric message budgets. Raw observations are also quantized to eight or sixteen bits and reconstructed with ordinary nonnegative total variation. Shared measurement operators, cached normals, metadata, and file overhead are accounted for separately. A small transmitted vector does not mean the whole system has that memory footprint.

measured projections=A B c+residual\begin{gathered}\text{measured projections}=A\,B\,c+\text{residual}\end{gathered}
B computes represented pixel averages; A is the supplied pixel-domain scanner model. Exact basis integration does not eliminate all measurement-model approximation.

The frontier rejects the proposal

At 1,156 coefficients, cardinal error is 0.063146 and cosine error is 0.055151, with the same 14,100-byte messages. Eight-bit raw plus TV reaches 0.042262 using 7,608 bytes. Cosine wins at every matched dimension. The raw control is both smaller and more accurate than the two larger cardinal messages. That is the result, not an inconvenient baseline to omit.

All selected cardinal and cosine dimensions, plus raw-TV controls, from the completed admission study. Error is on development measurement views, not ground-truth image pixels.
All selected cardinal and cosine dimensions, plus raw-TV controls, from the completed admission study. Error is on development measurement views, not ground-truth image pixels.

A different prior did not rescue it

A separately frozen diagnostic gives both compact spaces the same TV prior. The ranking remains unfavorable to cardinal within the stated budget. All six tighter compact solves miss their strict feasibility tolerance, so they are not certified optima. The paper reports this qualification and the complete trial accounting rather than implying that every possible spline reconstruction has been ruled out.

What would make compressed inspection useful?

The broader goal remains valuable: let an inspection system answer a useful new question without shipping every measurement. This experiment says that the tested cardinal message is not yet the right route. Showing the real reconstructions and complete error–byte frontier is the most informative way to communicate that result.

What a better inspection claim would need

The ambitious application is to answer a valuable new inspection question using fewer additional measurements. That requires actual defect or geometry ground truth, multiple specimens, and a strong targeted-acquisition comparator. Fixed-space algebra remains useful infrastructure, but it did not establish that capability here. The reserved views remain closed and the bounded study is finished.

Evidence & further reading

The links below distinguish the project record from foundational literature. This revised story does not add a new application-validation experiment.

  1. Measured inspection-memory admission and information boundaries. Daniel Schmitter (2026). Local archive snapshot.
  2. Experiment-family evidence map. Spline research archive (2026). Local archive snapshot.