Answering the Top FAQs on Camera Imaging Technologies

Color accuracy measures how accurately a camera reproduces real-world colors, ensuring realistic and consistent images. It's crucial for identifying objects, inspecting products, matching colors, and quality control. It is often measured using a standard color checker in the CIE LAB color space and is represented as Delta C (ΔC). Lower Delta E values indicate better color accuracy.

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White balance is a fundamental camera setting that establishes the true color of white, serving as a baseline for all other colors. This correction of color balance under varying lighting conditions is a key factor in ensuring accurate and natural-looking images.

Saturation refers to the degree of colour vibrancy or intensity in an image. High saturation colors are vibrant, while desaturated colors are muted. The saturation can be adjusted to provide a variety of visual effects, but over-saturation can result in unnatural colors.

The signal-to-noise ratio (SNR) measures the strength of the desired signal compared to background noise and is typically expressed in decibels. Higher SNR values indicate better image quality with more useful information and less noise.

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Gamma correction adjusts the luminance of a pixel to ensure accurate image representation in a standard color space like RGB, which is common in displays.

Dynamic range measures the range of light levels in a scene, from the darkest to the brightest areas. The camera's dynamic range is determined by its capacity to record these areas without clipping and with a good signal-to-noise ratio.

Multi-shutter speed capture : HDR captures multiple scene images using different shutter speeds, capturing varying light intensities to record bright, medium-lit, and dark areas. This can also be achieved with split pixel architecture, where pixels have different sensitivities.

Image combination : HDR technology uses algorithms to combine different exposures, creating a composite image that accurately represents bright and dark areas, preventing overexposure or underexposure.

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You can change the i-HDR settings through the Extension Unit control provided through the e-CAMView application for Windows OS and the QtCAM application for Linux OS.

LED Flicker Mitigation (LFM) reduces or eliminates flickering effects associated with LED lighting systems, such as traffic signals and signboards, due to repetitive ON/OFF cycles. This technique results in higher-quality images when capturing LED-based lights and signs.

Spectral sensitivity measures the response of an image sensor to different light wavelengths, which influences color reproduction and light capture. Cameras ensure accurate color reproduction in photographs with well-calibrated spectral sensitivity.

An image signal processor (ISP) in a camera processes raw images from a camera sensor. It handles tasks such as demosaicing, denoising, and auto adjustments to enhance the final image.

Multispectral imaging (MSI) captures images across specific wavelength ranges of the electromagnetic spectrum, covering visible light, ultraviolet (UV), near-infrared (NIR), short-wave infrared (SWIR), mid-wave infrared (MWIR), and long-wave infrared (LWIR) regions. Cameras use filters or detectors to isolate wavelength ranges, integrating multiple photodetectors per pixel. Consequently, every wavelength band has a spectral signature in a multidimensional dataset.

Image binning increases the adequate size of sensor pixels by combining the electric current of adjacent pixels, improving image quality in low-light situations by enhancing sensitivity.

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Image binning uses the demosaicing method, combining data from four neighboring pixels into a single "superpixel." This enhances performance in low-light environments but reduces the effective resolution to 1/4th of the sensors'.

Demosaicing produces full-color pixels in color cameras using a Bayer pattern by combining photosite data. It ensures accurate color representation by inferring missing color information.

ROI, or Region of Interest, enables users to focus on and capture the highest quality image within a selected frame area.

With multi-ROI, users can simultaneously focus on and optimize image quality for multiple predefined areas (ROIs) within a single frame. By processing only the selected regions, multi-ROI can improve processing speed, reduce data load, and enhance overall system efficiency.

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Yes, you can enable ROI functionality through customization to achieve faster frame rates.

An IMU detects movements and rotations across six degrees of freedom, including pitch, yaw, and roll, providing comprehensive data on an object's spatial orientation and movement.

IMUs track relative orientation and position, ensuring accurate spatial representation even in challenging lighting conditions. They also aid in camera stabilization by compensating for unwanted motion and reducing latency for quicker visual adjustments.

Pixels, or photosites, are tiny, light-sensitive components on a camera sensor that capture light to form images. The pixel size affects the sensor's ability to capture light, which is measured in microns.

Cameras with larger pixel sensors capture more light, improving image quality in low-light conditions. Smaller pixel sensors capture more details, making them suitable for high-detail capture applications.

Split-pixel HDR, often referred to as sub-pixel HDR, involves splitting each pixel on the sensor into two sub-pixels, allowing the camera to capture both bright and dark areas of a scene simultaneously. This technology is crucial in embedded vision systems as it enables the recording of a broader range of brightness levels while simultaneously decreasing motion blur and producing clearer, realistic images with more accurate color representation.

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A single pixel in an image capture system consists of large and small on-chip microlens (OCL). The SP2 OCL is located in the gap section of SP1, with a high-sensitivity pixel for brightly projecting dark subjects and a low-sensitivity pixel for saturating bright subjects. This combination creates a wide dynamic range, ensuring no loss of blackout or blowout in high-contrast scenes. This split or sub-pixel architecture helps the camera to capture a High Dynamic Range of 120dB.

Top view of the pixel architecture

Camera sensors produce color images using the Bayer pattern in 8, 10, or 12 bits. These images feature red, green, and blue color information distributed across each pixel. The Image Signal Processor (ISP) manages and refines the data to convert this raw sensor output into a fully processed image. The comparison image below illustrates the difference between a Bayer image and a processed image.

Bayer vs ISP processed image

SYNC Mode : Images are captured at fixed intervals based on a standard clock signal or external trigger. All operations occur at regular, predictable times. Multiple cameras can be synchronized to capture images simultaneously, which is helpful for applications like 3D imaging or high-speed events from different angles.

Async mode : Images are captured independently without relying on a fixed clock signal. Each capture event can occur anytime, often triggered by specific events or conditions. Cameras operate independently, which can be helpful in systems where different cameras must capture images at other times.