The resolving power of a lens is a very important parameter in the design of embedded vision and machine vision systems. It determines how finely the system can recognize and distinguish image details. Understanding and optimizing this parameter ensures high performance and high accuracy of the vision system.
This article will serve as your professional guide to camera module and optical design, and will explore the various aspects of lens resolution. We will explain its meaning, compare the resolving power of photographic lenses to that of the human eye, and explore how to solve practical pain points in the embedded vision field by optimizing lens selection.
What is resolving power? Core definition and physical foundation
What is resolving power? In simple terms, resolving power refers to the ability of an optical system (such as a lens or a microscope) to distinguish between two closely adjacent points. It measures how much detail the system can see. If two points are too close together, the optical system may recognize them as a blurred spot of light.
This concept is based on the diffraction limit. When light passes through an aperture, it diffracts, causing a point source of light to form an Airy disk on the image plane. When the Airy disks of two point sources overlap, the system has difficulty resolving them. Higher resolving power means a smaller minimum distance that the system can distinguish.
Therefore, resolving power is a key performance indicator for measuring the image clarity and detail capture ability of an optical system. For high-precision machine vision applications such as defect detection and dimensional measurement, lenses with high resolving power are important.
Resolving power of photographic lenses: pixels, MTF and practical considerations
What is the resolving power of a photographic lens? For photographic lenses, the resolving power is usually determined by multiple factors, not just the lens itself. It is a complex multivariate problem involving optical design, manufacturing accuracy, and matching with the image sensor (pixel size).
A common metric is line pairs per millimeter (lp/mm), which indicates how many black and white line pairs the lens can distinguish within one millimeter. The higher the number, the higher the resolution. In addition, the modulation transfer function (MTF) curve is a more comprehensive evaluation tool, which shows the efficiency of the lens in contrast transfer at different spatial frequencies.
However, simply looking at the nominal resolution of a lens is not enough. In actual use, the resolving power of a lens is also affected by aperture size (diffraction effect), focus accuracy, field curvature, and chromatic aberration. For embedded vision engineers, it is crucial to understand these practical limitations and choose lenses that match the sensor.
The resolving power of the human eye: biological optics and perception limits
What is the resolving power of an eye? As a biological optical system, the resolving power of the human eye is also limited by diffraction and the density of retinal photoreceptor cells. Under ideal lighting conditions, the theoretical resolving power of the human eye is about 1 arc minute, which is equivalent to resolving two points about 6 mm apart at a distance of 20 meters.
This corresponds to a resolution of about 1.75 line pairs per millimeter, which is not particularly high compared to some high-quality industrial lenses. However, the human eye can compensate for many optical defects through mechanisms such as blinking, pupil adjustment, and brain image processing, providing a very flexible and efficient visual experience.
Understanding the resolution limit of the human eye helps us better understand the possibility of machine vision surpassing the human eye in certain scenarios, as well as the visual perception characteristics that need to be considered when designing human-machine interaction interfaces. Machine vision systems often pursue accuracy and automation that exceed what the human eye can perceive.
How to calculate resolution? The use of reso calculator
In optical design and selection, we often need to estimate or calculate the resolution of a lens. A basic calculation method is based on the Rayleigh Criterion. The following is the calculation formula for the minimum resolvable angular distance
Where λ is the wavelength of light and D is the effective aperture diameter of the lens.
Based on this formula, we can derive the minimum resolvable distance in real space. There are also many reso calculator tools and formulas on the market that can help engineers quickly estimate the theoretical resolution limit. For example, when considering the sensor pixel size, we need to ensure that the resolution of the lens is sufficient to focus enough light onto a single pixel, otherwise the potential of the pixel will not be fully utilized.
These calculators can help engineers quickly evaluate the theoretical resolution that a system can achieve given focal length, aperture, and sensor parameters. This is critical to avoid "overkill" or "a small horse pulling a big cart" situations, effectively controlling costs and meeting performance requirements.
Optimizing Lens Resolution: Advantages and Limitations
For engineers in the field of embedded vision, resolving power of lens has both advantages and limitations.
Advantages:
- Achieve high-precision detection: High-resolution lenses enable the system to identify micron-level defects, such as tiny flaws in semiconductor inspection and PCB inspection, which is difficult to achieve with traditional methods.
- Support small target recognition: In drones and security monitoring, even if the target is small or far away, high-resolution lenses can provide enough details to support accurate recognition and tracking.
- Improve system reliability: Clear, high-detail image input can significantly improve the accuracy and robustness of back-end image processing algorithms and reduce false positives and false negatives.
Limitations:
- Balance between cost and performance: High resolution usually means more complex optical design and more expensive materials. How to choose the best performance lens within the budget is a common problem.
- Aberration control: High-resolution lenses have higher requirements for aberration control. Chromatic aberration, spherical aberration, field curvature, etc. will reduce the actual resolving power, especially at the edge of the image.
- Matching with the sensor: The resolution of the lens needs to match the pixel size and noise level of the image sensor. If the sensor pixel is too large, the lens details cannot be fully utilized; if the pixel is too small, it may be limited by the optical diffraction limit of the lens.
- Integration and calibration challenges: High-resolution systems have higher requirements for mechanical accuracy, focus accuracy and calibration. Any slight deviation may affect the final image quality.
Summary
Lens resolution (resolving power of lens) is a core element of the success of embedded vision systems. It is not just an optical parameter, but also a key factor affecting system performance, cost and application range. Understanding what is resolving power, mastering the use of reso calculator, and being able to compare the resolving power of a photographic lens with the resolving power of an eye in practice are crucial for embedded vision engineers.
By accurately selecting and integrating high-resolution lenses, combined with appropriate image sensors and algorithms, we can build intelligent vision systems that exceed the human eye and meet industrial-grade accuracy requirements. This not only solves many pain points in the fields of industrial inspection and autonomous driving, but also opens up new possibilities for future intelligent applications.
Earlier, we mentioned some resources related to lenses. Those who are interested can take a look.
- What is a liquid lens camera?and the difference with traditional Lens
- Liquid Lens Autofocus vs Voice Coil Motor (VCM) Autofocus: A Comprehensive Guide
- What Is Field of View (FoV)? Explained for Camera Modules and Lenses
- The role of lens in camera module?How Optics Define Image Quality & Performance?
Sinoseen helps with resolving power of lens
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