Imaging Lens:- Introduction to Modulation Transfer Function

When optical designers attempt to compare the performance of optical systems, a commonly used measure is the modulation transfer function (MTF). MTF is used for components as simple as a spherical singlet lens to those as complex as a multi-element telecentric Edmund Optics imaging lens assembly. In order to understand the significance of MTF, consider some general principles and practical examples for defining MTF including its components, importance, and characterization.

THE COMPONENTS OF MTF

To properly define the modulation transfer function, it is necessary to first define two terms required to truly characterize image performance: resolution and contrast.

Resolution of Imaging Lens

Resolution is an imaging system's ability to distinguish object detail. It is often expressed in terms of line-pairs per millimeter (where a line-pair is a sequence of one black line and one white line). This measure of line-pairs per millimeter (lp/mm) is also known as frequency. The inverse of the frequency yields the spacing in millimeters between two resolved lines. Bar targets with a series of equally spaced, alternating white and black bars (i.e. a 1951 USAF target or a Ronchi ruling) are ideal for testing system performance. For a more detailed explanation of test targets, view Choosing the Correct Test Target. For all imaging optics, when imaging such a pattern, perfect line edges become blurred to a degree (Figure 1). High-resolution images are those which exhibit a large amount of detail as a result of minimal blurring. Conversely, low-resolution images lack fine detail.

A practical way of understanding line-pairs is to think of them as pixels on a camera sensor, where a single line-pair corresponds to two pixels (Figure 2). Two camera sensor pixels are needed for each line-pair of resolution: one pixel is dedicated to the red line and the other to the blank space between pixels. Using the aforementioned metaphor, image resolution of the camera can now be specified as equal to twice its pixel size.

Correspondingly, object resolution is calculated using the camera resolution and the primary magnification (PMAG) of the imaging lens (Equations 1 – 2). It is important to note that these equations assume the imaging lens contributes no resolution loss.

Contrast/Modulation

Consider normalizing the intensity of a bar target by assigning a maximum value to the white bars and zero value to the black bars. Plotting these values results in a square wave, from which the notion of contrast can be more easily seen (Figure 3). Mathematically, contrast is calculated with Equation 3:

When this same principle is applied to the imaging example in Figure 1, the intensity pattern before and after 
imaging can be seen (Figure 4). Contrast or modulation can then be defined as how faithfully the minimum and maximum intensity values are transferred from object plane to image plane.
To understand the relation between contrast and image quality, consider an imaging lens with the same resolution as the one in Figure 1 and Figure 4, but used to image an object with a greater line-pair frequency. Figure 5 illustrates that as the spatial frequency of the lines increases, the contrast of the image decreases. This effect is always present when working with imaging lenses of the same resolution. For the image to appear defined, black must be truly black and white truly white, with a minimal amount of grayscale between.

In imaging applications, the imaging lens, camera sensor, and illumination play key roles in determining the resulting image contrast. The lens contrast is typically defined in terms of the percentage of the object contrast that is reproduced. The sensor's ability to reproduce contrast is usually specified in terms of decibels (dB) in analog cameras and bits in digital cameras.



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About MVRPL

Video Surveillance, Machine Vision, Intelligent Transportation Systems, Life Sciences, Defense, OEM, Computar CCTV lenses are employed extensively in high-security applications such as airports, banks, government buildings and commercial industries.

We are constantly engaged in researching the latest CCTV technology in order to meet the security challenges of today to ensure you a safe and secure future.

Contact Us at:

Menzel Vision & Robotics Pvt Ltd
Address: 4, A-Wing, Bezzola Complex,
Sion Trombay Road, Chembur
400071 Mumbai, India
Tel:(+91) 22 67993158
Fax: (+91) 22 67993159
Mobile:+91 9323786005 / 9820143131
E-mail: info@mvrpl.com
Website : http://www.mvrpl.com

11 Best Practices for Better Imaging with Edmund Optics

11 Best Practices for Better Imaging with Edmund Optics


Whether your application is in machine vision, the life sciences, security, or traffic solutions, understanding the fundamentals of imaging technology significantly eases the development and deployment of sophisticated imaging systems. While advancements in sensor and illumination technologies suggest limitless system capabilities, there are physical limitations in the design and manufacture of these technologies. Optical components are not an exception to such limitations, and optics can often be the limiting factor in a system’s performance. The content provided in this guide is designed to help you specify an imaging system, maximize your system’s performance, and minimize cost.

We have compiled a number of best practices for creating sophisticated, cost-effective imaging systems that are applicable for most applications. While the following list is nearly exhaustive and should be considered when designing any imaging system, every application is unique and additional considerations may be required.

Edmund Optics Best Practice #1: Bigger, in many cases, is better. Allow ample room for the imaging system.

Understanding a system’s space requirements before building is especially true for high resolution and high magnification requirements. While recent advancements in consumer camera technology have yielded strong results in a small package, they still do not approach the capabilities required for even intermediate-level industrial imaging systems – partially because of their size limitations. Many applications can require complex light geometries, large diameter and long length lenses, and large cameras, in addition to the cabling and power sources required to operate some of the equipment. Avoid having to make sacrifices to system performance just because the system’s space requirements were not considered. It is often advantageous to specify the vision portion of a system first, as it is typically easier to arrange the electronics and mechanics around the vision portion rather than the other way around. It is also important to remember that the illumination scheme is part of the vision system, and the geometry of the object under inspection can often necessitate the use of a large light source such as a diffuse dome (see EO Best Practice #4).

Edmund Optics Best Practice #2: Don’t believe your eyes.

The human eye and brain work together to form an extremely advanced imaging and analysis system that is capable of filling in information that is not necessarily there. Additionally, humans see and process contrast differently than imaging systems. Software analysis should be used to ensure image quality and performance requirements are met. Images that look good to a human viewer may not be usable with an algorithm.

Edmund Optics Best Practice #3: Danger! Don’t get to close.

Due to the constraints of physics, attempting to look at fields of view that are too large relative to a lens’s working distance places excessive demands on the design of the optical component and can decrease system performance. It is recommended that a working distance of two to four times the desired field view be used to maximize performance while minimizing cost. Remember EO Best Practice #1 and consider the imaging system’s space requirement before building the system.
This practice also applies to the relationship between sensor size and focal length. It is best to have focal length to sensor diagonal ratios of two to four to maximize performance.

Best Practice #1 and #3:

If a 100mm field of view is required, it is recommended that the system’s working distance be 200 - 400mm. It may be possible that the system’s performance requirements can be met at WD to FOV ratios approaching or exceeding 1 to 1, however, potentially significant cost and performance tradeoffs may be necessary.
Both lenses in Figure 1a and Figure 1b are imaging the same field of view onto the same sensor, but the lens in 1a has a working distance of half of its field of view, while the lens in 1b has a working distance of 3X its field of view. The light passes through the lens in a at extreme angles and the light on the edges of the field of view (magenta/red) have a much longer distance to travel than the light in the center of the field of view (blue). In contrast, the lens in 1b achieves the same field of view at shallower angles with a smaller path length difference. As a result, the lens in 1b features a much less complex lens design and provides superior performance at a lower cost.

Read More About 11 Best Practices for Better Imaging with Edmund Optics

About MVRPL

Video Surveillance, Machine Vision, Intelligent Transportation Systems, Life Sciences, Defense, OEM, Computar CCTV lenses are employed extensively in high-security applications such as airports, banks, government buildings and commercial industries.

We are constantly engaged in researching the latest CCTV technology in order to meet the security challenges of today to ensure you a safe and secure future.

Contact Us at:

Menzel Vision & Robotics Pvt Ltd
Address: 4, A-Wing, Bezzola Complex,

Sion Trombay Road, Chembur
400071 Mumbai, India
Tel:(+91) 22 67993158
Fax: (+91) 22 67993159
Mobile:+91 9323786005 / 9820143131
E-mail: info@mvrpl.com
Website : http://www.mvrpl.com