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Oversampled binary image sensor

Oversampled binary image sensor is a science 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 Oversampled binary image sensor rather than just read about it. In short: An oversampled binary image sensor is an image sensor with non-linear response capabilities reminiscent of traditional photographic film. Each pixel in the sensor has a binary response, giving only a one-bit quantized measurement of the local light intensity.

Oversampled binary image sensor — main illustration
Oversampled binary image sensor — illustration

Key takeaways

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

Reference excerpt

An oversampled binary image sensor is an image sensor with non-linear response capabilities reminiscent of traditional photographic film. Each pixel in the sensor has a binary response, giving only a one-bit quantized measurement of the local light intensity. The response function of the image sensor is non-linear and similar to a logarithmic function, which makes the sensor suitable for high dynamic range imaging.

Working principle Before the advent of digital image sensors, photography, for the most part of its history, used film to record light information. At the heart of every photographic film are a large number of light-sensitive grains of silver-halide crystals. During exposure, each micron-sized grain has a binary fate: Either it is struck by some incident photons and becomes "exposed", or it is missed by the photon bombardment and remains "unexposed". In the subsequent film development process, exposed grains, due to their altered chemical properties, are converted to silver metal, contributing to opaque spots on the film; unexposed grains are washed away in a chemical bath, leaving behind the transparent regions on the film. Thus, in essence, photographic film is a binary imaging medium, using local densities of opaque silver grains to encode the original light intensity information. Thanks to the small size and large number of these grains, one hardly notices this quantized nature of film when viewing it at a distance, observing only a continuous gray tone. The oversampled binary image sensor is reminiscent of photographic film. Each pixel in the sensor has a binary response, giving only a one-bit quantized measurement of the local light intensity. At the start of the exposure period, all pixels are set to 0. A pixel is then set to 1 if the number of photons reaching it during the exposure is at least equal to a given threshold q. One way to build such binary sensors is to modify standard memory chip technology, where each memory bit cell is designed to be sensitive to visible light. With current CMOS technology, the level of integration of such systems can exceed 109~1010 (i.e., 1 giga to 10 giga) pixels per chip. In this case, the corresponding pixel sizes (around 50~nm ) are far below the diffraction limit of light, and thus the image sensor is oversampling the optical resolution of the light field. Intuitively, one can exploit this spatial redundancy to compensate for the information loss due to one-bit quantizations, as is classic in oversampling delta-sigma converters. Building a binary sensor that emulates the photographic film process was first envisioned by Fossum, who coined the name digital film sensor (now referred to as a quanta image sensor). The original motivation was mainly out of technical necessity. The miniaturization of camera systems calls for the continuous shrinking of pixel sizes. At a certain point, however, the limited full-well capacity (i.e., the maximum photon-electrons a pixel can hold) of small pixels becomes a bottleneck, yielding very low signal-to-noise ratios (SNRs) and poor dynamic ranges. In contrast, a binary sensor whose pixels need to detect only a few photon-electrons around a small threshold q has much less requirement for full-well capacities, allowing pixel sizes to shrink further.

Imaging model

Lens

Consider a simplified camera model shown in Fig.1. The λ 0 ( x ) {\displaystyle \lambda _{0}(x)} is the incoming light intensity field. By assuming that light intensities remain constant within a short exposure period, the field can be modeled as only a function of the spatial variable x {\displaystyle x} . After passing through the optical system, the original light field λ 0 ( x ) {\displaystyle \lambda _{0}(x)} gets filtered by the lens, which acts like a linear system with a given impulse response. Due to imperfections (e.g., aberrations) in the lens, the impulse response, a.k.a. the point spread function (PSF) of the optical system, cannot be a Dirac delta, thus, imposing a limit on the resolution of the observable light field. However, a more fundamental physical limit is due to light diffraction. As a result, even if the lens is ideal, the PSF is still unavoidably a small blurry spot. In optics, such diffraction-limited spot is often called the Airy disk, whose radius R a {\displaystyle R_{a}} can be computed as

R a = 1.22 w f , {\displaystyle R_{a}=1.22\,wf,}

where w {\displaystyle w} is the wavelength of the light and f {\displaystyle f} is the F-number of the optical system. Due to the lowpass (smoothing) nature of the PSF, the resulting λ ( x ) {\displaystyle \lambda (x)} has a finite spatial-resolution, i.e., it has a finite number of degrees of freedom per unit space.

Sensor

… excerpt ends here. Continue reading the full article.

Illustrations

Oversampled binary image sensor: Fig.2 The model of the binary image sensor. The pixels (shown as "buckets") collect photons, the numbers of which are compared against a quantization threshold q. In the figure, we illustrate the case when q = 2. The pixel outputs are binary: 
  
    
      
        
          b
          
            m
          
        
        =
        1
      
    
    {\displaystyle b_{m}=1}
  
 (i.e., white pixels) if there are at least two photons received by the pixel; otherwise, 
  
    
      
        
          b
          
            m
          
        
        =
        0
      
    
    {\displaystyle b_{m}=0}
  
 (i.e., gray pixels).
Fig.2 The model of the binary image sensor. The pixels (shown as "buckets") collect photons, the numbers of which are compared against a quantization threshold q. In the figure, we illustrate the case when q = 2. The pixel outputs are binary: b m = 1 {\displaystyle b_{m}=1} (i.e., white pixels) if there are at least two photons received by the pixel; otherwise, b m = 0 {\displaystyle b_{m}=0} (i.e., gray pixels).
Oversampled binary image sensor: Fig.4 Reconstructing an image from the binary measurements taken by a SPAD[10] sensor, with a spatial resolution of 32×32 pixels. The final image (lower-right corner) is obtained by incorporating 4096 consecutive frames, 11 of which are shown in the figure.
Fig.4 Reconstructing an image from the binary measurements taken by a SPAD[10] sensor, with a spatial resolution of 32×32 pixels. The final image (lower-right corner) is obtained by incorporating 4096 consecutive frames, 11 of which are shown in the figure.

Worked examples

Example 1 — a first encounter with Oversampled binary image sensor

Start with the simplest possible case. Write down what Oversampled binary image sensor claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, 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 Oversampled binary image sensor 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 Oversampled binary image sensor 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 Oversampled binary image sensor

In research
Oversampled binary image sensor appears in science 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 Oversampled binary image sensor 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
Oversampled binary image sensor is common in secondary-school and first-year university syllabi. It links to neighbouring topics Digital electronics, Digital photography, Digital signal processing, so understanding it makes those chapters shorter.
In everyday life
Look for Oversampled binary image sensor 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 Oversampled binary image sensor in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Oversampled binary image sensor 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 Oversampled binary image sensor out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Oversampled binary image sensor in simple terms?

An oversampled binary image sensor is an image sensor with non-linear response capabilities reminiscent of traditional photographic film. Each pixel in the sensor has a binary response, giving only a one-bit quantized measurement of the local light intensity.

Why does Oversampled binary image sensor matter?

Because it connects several science 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 Oversampled binary image sensor?

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 Oversampled binary image sensor.

Tags

  • Digital electronics
  • Digital photography
  • Digital signal processing
  • Image processing
  • Image sensors

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