top of page

Digital Imaging Sensors - An Introduction

Updated: Mar 25

In the current age of AI, imaging systems are evolving to replace the human eye. Imaging is an exponentially growing mode of data acquisition and collection. Imaging is used to gather all kinds of data such as age, gender, height etc. of people standing at signal, using a vending machine, visiting a shop, crossing the road, passing by a kiosk, registering at some conference, ordering a coffee, boarding a flight etc. Apart from people, imaging also helps collect data on vehicles, packages, animals, birds, fishes, medicines, groceries and so on.

This blog talks about the image sensors and their high-level categorization.

Understanding Digital Imaging Sensors

An imaging sensor is a device/subsystem/chipset that conveys information used to make an image. It does so by converting the variable attenuation of light waves (as they pass through or reflect off objects) falling on the sensor area into electrical signals that can be understood by a CPU.

They are instrumental in enabling the creation of digital images across a diverse array of applications, including surveillance, medical imaging, industrial inspection, and consumer electronics.

Categorization of Digital Imaging Sensors

Digital imaging sensors can be categorized in terms of the below listed aspects.

Based on Building Blocks

a. CCD – Charge-Coupled Device

CCD sensors utilize an array of capacitors to transport charge across the chip to be converted into electrical signals. They offer high image quality and low noise, making them ideal for applications where precision and sensitivity are paramount, such as scientific imaging and astronomy.

b. CMOS – Complementary Metal Oxide Semiconductor

CMOS sensors employ individual light-sensitive pixels with associated circuitry to capture and convert light into electrical signals. They are more energy-efficient and cost-effective compared to CCD sensors, making them prevalent in consumer electronics, mobile devices, and automotive cameras.

Based on Pixel Scanning Methodologies

Imaging sensors can also be distinguished based on their pixel scanning methodologies, each offering distinct advantages suited to specific applications.

a. Global Shutter

Global shutter sensors capture the entire image simultaneously, eliminating motion artifacts and distortion commonly associated with rolling shutter sensors. They are well-suited for applications requiring precise motion capture and high-speed imaging, such as sports photography and machine vision systems.

b. Rolling Shutter

Rolling shutter sensors capture images by sequentially scanning rows of pixels, leading to potential distortions in fast-moving subjects or when capturing rapid changes in illumination. However, they are cost-effective and widely used in applications such as consumer photography and video recording.

c. Global Reset Release

Global reset release sensors combine the benefits of global shutter and rolling shutter technologies, allowing for simultaneous reset and readout of pixels. This results in improved image quality and reduced motion artifacts, making them suitable for demanding applications in scientific imaging and industrial inspection.

Based on Output Formats

The output format of digital imaging sensors plays a crucial role in determining the fidelity and versatility of captured data.

a. Raw Bayer

Raw Bayer output format stores color information using a mosaic pattern of red, green, and blue pixels. While offering high resolution and flexibility for image processing, it requires demosaicing algorithms to reconstruct full-color images accurately.

b. Monochrome

Monochrome output format captures images in grayscale, offering enhanced sensitivity and dynamic range compared to color sensors. It is commonly used in applications where precise luminance information is critical, such as medical imaging and machine vision.

Based on Output Interfaces

The interface through which imaging data is transmitted is another significant aspect that influences system compatibility and performance.


MIPI (Mobile Industry Processor Interface) is a standard interface widely adopted in mobile devices and embedded systems for high-speed data transfer between imaging sensors and processing units. It offers low power consumption and high bandwidth, making it suitable for real-time image capture and processing.

b. DVP

DVP (Digital Video Port) is a parallel interface commonly used in consumer electronics and industrial cameras for transmitting digital video data. While offering simplicity and compatibility with legacy systems, it has limitations in terms of bandwidth and scalability.

c. sLVDS

sLVDS (Sub-LVDS) is a low-voltage differential signaling interface designed for high-speed data transmission in industrial imaging applications. It offers high noise immunity and bandwidth, making it suitable for demanding environments where reliability and performance are critical.

We have covered the four categorization of imaging sensor. Each of the type serve specific purpose and use case. There is no one type that fits all requirement. Based on the use case, we shall have to decide which type of sensor helps us to address the requirement the best.

Regami's Expertise with Digital Imaging Sensors

We, at Regami, have had the pleasure of working with variety of imaging sensors from companies such as On Semiconductors, Sony, Omnivision etc. Please let us know if you have any queries. The team at Regami shall be glad to address them.

We are expecting questions like - How do we select which type of sensor to use? What are the pros and cons of each type? Are there any further sub-categories we need to be aware? We shall cover them individually in the upcoming blogs.


Sarvesh Rajagopal


bottom of page