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Single-pixel imaging

Single-pixel imaging is a physics topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Single-pixel imaging rather than just read about it. In short: Single-pixel imaging is a computational imaging technique for producing spatially-resolved images using a single detector instead of an array of detectors (as in conventional camera sensors). A device that implements such an imaging scheme is called a single-pixel camera.

Single-pixel imaging — main illustration
Single-pixel imaging — illustration

Key takeaways

  • Single-pixel imaging belongs to physics; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Single-pixel imaging to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Single-pixel imaging from memory before moving on to harder problems.

Reference excerpt

Single-pixel imaging is a computational imaging technique for producing spatially-resolved images using a single detector instead of an array of detectors (as in conventional camera sensors). A device that implements such an imaging scheme is called a single-pixel camera. Combined with compressed sensing, the single-pixel camera can recover images from fewer measurements than the number of reconstructed pixels. Single-pixel imaging differs from raster scanning in that multiple parts of the scene are imaged at the same time, in a wide-field fashion, by using a sequence of mask patterns either in the illumination or in the detection stage. A spatial light modulator (such as a digital micromirror device) is often used for this purpose. Single-pixel cameras were developed to be simpler, smaller, and cheaper alternatives to conventional, silicon-based digital cameras, with the ability to also image a broader spectral range. Since then, they have been adapted and demonstrated to be suitable for numerous applications in microscopy, tomography, holography, ultrafast imaging, FLIM and remote sensing.

History The origins of single-pixel imaging can be traced back to the development of dual photography and compressed sensing in the mid-2000s. Seminal papers by Takhar et al. and Duarte et al. at Rice University concretised the foundations of the single-pixel imaging technique. It also presented a detailed comparison of different scanning and imaging modalities in existence at that time. These developments were also one of the earliest applications of the digital micromirror device (DMD), developed by Texas Instruments for their DLP projection technology, for structured light detection. Soon, the technique was extended to computational ghost imaging, terahertz imaging, and 3D imaging. Systems based on structured detection were often termed single-pixel cameras, whereas those based on structured illumination were often referred to as computational ghost imaging. By using pulsed-lasers as the light source, single-pixel imaging was applied for time-of-flight measurements used in depth-mapping LiDAR applications. Apart from the DMD, different light modulation schemes were also experimented with liquid crystals and LED arrays. In the early 2010s, single-pixel imaging was exploited in fluorescence microscopy, for imaging biological samples. Coupled with the technique of time-correlated single photon counting (TCSPC), the use of single-pixel imaging for compressive fluorescence lifetime imaging microscopy (FLIM) has also been explored. Since the late 2010s, machine learning techniques, especially Deep learning, have been increasingly used to optimise the illumination, detection, or reconstruction strategies of single-pixel imaging.

Principles

Theory

… excerpt ends here. Continue reading the full article.

Illustrations

Single-pixel imaging: Schematic of a single-pixel camera using a DMD. The transmitted light (white) from the sample (blue) is modulated by the DMD and collected by a single-pixel detector.[1]
Schematic of a single-pixel camera using a DMD. The transmitted light (white) from the sample (blue) is modulated by the DMD and collected by a single-pixel detector.[1]
Single-pixel imaging: Compressed sensing represented as sampling a signal ( z {\displaystyle z} ) in a basis Ψ {\displaystyle \Psi } . Here x {\displaystyle x} is the coefficient vector of z {\displaystyle z} which is sparse (shown as having only a few coloured dots) in Ψ {\displaystyle \Psi } . The inner product of a rank-deficient random matrix P {\displaystyle P} (shown by the randomly-coloured dots) with z {\displaystyle z} gives the measurement vector y {\displaystyle y} . Under certain conditions, the signal z {\displaystyle z} can be reconstructed (nearly) accurately.
Compressed sensing represented as sampling a signal ( z {\displaystyle z} ) in a basis Ψ {\displaystyle \Psi } . Here x {\displaystyle x} is the coefficient vector of z {\displaystyle z} which is sparse (shown as having only a few coloured dots) in Ψ {\displaystyle \Psi } . The inner product of a rank-deficient random matrix P {\displaystyle P} (shown by the randomly-coloured dots) with z {\displaystyle z} gives the measurement vector y {\displaystyle y} . Under certain conditions, the signal z {\displaystyle z} can be reconstructed (nearly) accurately.

Worked examples

Example 1 — a first encounter with Single-pixel imaging

Start with the simplest possible case. Write down what Single-pixel imaging claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In physics, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Single-pixel imaging before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Single-pixel imaging ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Single-pixel imaging

In research
Single-pixel imaging appears in physics research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Single-pixel imaging in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Single-pixel imaging is common in secondary-school and first-year university syllabi. It links to neighbouring topics Optical imaging, Signal processing, so understanding it makes those chapters shorter.
In everyday life
Look for Single-pixel imaging outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Single-pixel imaging in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Single-pixel imaging means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Single-pixel imaging out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Single-pixel imaging in simple terms?

Single-pixel imaging is a computational imaging technique for producing spatially-resolved images using a single detector instead of an array of detectors (as in conventional camera sensors). A device that implements such an imaging scheme is called a single-pixel camera.

Why does Single-pixel imaging matter?

Because it connects several physics ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Single-pixel imaging?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Single-pixel imaging.

Tags

  • Optical imaging
  • Signal processing

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