Factors that determine the Quality of Image Sensor 

Image Sensor

What is an Image Quality? 

Image refers to any visual or aural representation of something that helps us to see the world around us without actually seeing the original object. The image in the context of digital communications is a visual representation of a database, like an image on a map, in a photograph, or in a system, and can represent an item, an area, a scenario, a moment in time, an event, or a person. 

A high-quality image doesn’t always necessarily mean that it is bright, precise, and contrasted. The importance of image quality, which goes far beyond brightness and sharpness, cannot be overstated. When the camera uses the light from your sensor and processes it to create an appealing image, there is a significant amount of arithmetic and processing required. However, digital cameras and smartphones are managing this in an energy-efficient manner because of advanced image signal processors (ISPs).  

What effect do these aspects have on the quality of an image? Let’s take a closer look. This article will take you through certain terminologies that are considered analogous to sensor image quality. Understanding these terminologies shall help with the identification of the right sensor for the application.  

Features of Imaging Sensor  

Image quality and flexibility are directly proportional to a number of characteristics, including pixel size, resolution, and responsiveness. Furthermore, elements influencing quality include the brightness and uniformity of lighting, contrast, resolution, geometry, colour accuracy, and colour discrimination of an examined image. Therefore, this article describes the characteristics of the imaging sensor that influence image quality. 

The imaging sensor datasheets primarily talk about the following aspects: 

  • Sensor Format 
  • Pixel Size 
  • Resolution 
  • SNR 
  • Responsivity
  • Dynamic Range 

Let’s take a look at each one in detail. 

Sensor Format 

We come across specifications that talk about sensor format being 1/3” or 1/2.3” and so on. What does this indicate? 

Sensor format, also known as “optical format” or “sensor size,” corresponds to the size of a digital camera’s image sensor. The value represents the diagonal measurement of the sensor’s active image size. The inch here refers to the optical form factor. The optical form factor for a 1″ sensor is 16mm. This is a throwback to the days of tube cameras, when the image format of a tube placed in a 1″ deflection coil was referred to as 1″ format. To provide you a clear grasp of image sensor format, a detailed explanation was provided under the topic Image Sensor Format: A Consideration When Choosing a Camera Sensor. 

The common formats that we come across are:


Pixel Size 

Pixels express themselves in images, such as when you be seeing a visual in the image below that expresses disappointment. 


The pixel is the smallest element on the sensor that converts the energy from light (photons) to electrons, which are then digitized on the sensor to give us an image. The size of each pixel reflects how many photons it can accept throughout the time the sensor is exposed to light. The larger the pixel size, the lighter it accepts, delivering us with a better image. 

However, technology is improving by leaps and bounds, allowing us to produce higher-quality images with smaller pixel sizes. These improvements reduce the size of the sensor. 



The resolution is frequently brought up in discussions on image quality. Essentially, resolution refers to the number of pixels in the image. The total number of pixels in a picture can be calculated by multiplying the width and height of the image by the resolution. The sensor’s pixel count gives an idea of the anticipated image quality. 

However, image quality is determined by the use case and application. For instance, a higher resolution camera is anticipated if the camera is utilized for OCR or wide-angle image capture to ensure that more pixels can cover the entire area. More pixel’s equal greater precision. It establishes that a greater PPI equals a higher image resolution, which also equates to a higher image quality. 

Dot pitch is a measurement used to quantify an image’s sharpness. A lower value corresponds to a sharper image and is expressed in millimetres (mm). The distance between the centre of one pixel and the neighbouring pixel is known as the dot pitch. Depending on its resolution, an image quality with a lower dot pitch is said to be better. 

Although lighting may not be taken into account when determining image quality, it is just as crucial as the camera. Light is necessary to create the visuals. Images taken in low light are also hazy and lack sharpness and detail. Insufficient lighting also affects colours, lowering the overall quality of an image. Proper lighting will result in better quality. However, poor lighting will degrade the quality. High resolution sensors are now being used that can provide improved sensitivity even in low-light conditions as technology advances constantly. We discuss this in the responsivity section. 

Signal to Noise Ratio (SNR) 


As the name indicates, it is the ratio of healthy signal caused by light falling on the sensor to the unwanted noise. We can consider this as one of the most significant measurements of image quality. Sensors with higher SNR produce a cleaner and sharper image of the object. Low SNR will have some artifacts in the image due to different levels of noise in the captured image. 

For each sensor, you can find the SNR curve that talks about the SNR comparison of the photons per pixel. We must check the relevant part of the curve based on the use case. 

For example, for low light applications, we must examine the segment of the curve that exhibits fewer photographs per pixel and read the related SNR. When it comes to bright light applications, we must read the curve suggesting higher photographs per pixel and evaluate the SNR related to it. A camera that is efficient in low light does not have to be the most effective in bright light. 


Responsivity is a measure of the electrical output per optical input. The responsivity value indicates the sensor’s capability to produce good images under low light conditions. The higher responsivity indicates that lesser photons are sufficient to create good electrical output. 

The optical input varies with wavelength. Thus, the responsivity curve or Quantum Efficiency curve shows the electrical output for different wavelengths of the input light. You must test the curve at the required wavelength range based on your use case. 

Dynamic Range 

The dynamic range of a camera is a measure of how effectively it can reproduce features in both bright and dark areas. The broadest range of light that a digital camera sensor or sheet of film can capture is known as maximum dynamic range. Stops are used to assess dynamic range. Each stop represents a doubling of the brightness that is collected. Even the most advanced DSLR and mirrorless cameras can only capture images with a dynamic range of about 14 stops, compared to the human eye’s 20 stops. 


Compare the images on the left and right sides of the above photograph. We can see that the right image generated more detailed results than the left image. When compared to the left image, the right image was taken using a better dynamic range camera. 

Summing Up 

It’s essential to bear in mind the aforementioned factors while considering the image quality. These aspects of image quality might show where a digital camera system’s performance needs to be enhanced when properly assessed. The next time you shop for a camera, keep sensor size in account. Depending on your requirements, Vadzo’s solutions specialists may help you choose the ideal imaging sensor for your application.  

If anything, the sensor size is important because it is responsible for gathering the light to create the image. 

Feel free to contact us if you have any query.