What is Image Quality

Discover a world where every pixel tells a story.

ISP (Image Signal Processing) tuning refers to the process of optimizing the camera’s image processing algorithms to improve the quality of the photos and videos captured. It involves adjusting various settings, such as white balance, noise reduction, color accuracy, sharpness, contrast, and dynamic range. ISP tuning ensures that the camera sensor produces the best possible image output, enhancing details, colors, and clarity under different lighting conditions. The goal is to deliver consistent, high-quality images and videos across a variety of devices and environments.

Video explanation

Image quality explained

Video explanation

The journey of an image

Sensor raw image – The camera sensor captures light and records it as unprocessed raw data.
Calculating the perfect exposure – The camera’s processor automatically calculates optimal exposure settings to ensure the image isn’t too dark or too bright.
Lens shading correction – The camera applies lens shading correction to adjust for any darkening or color shifts around the edges of the image (vignetting)
Demosaicing: Creating a full-color image – Since camera sensors capture only one color per pixel, the camera processor performs demosaicing to estimate the missing colors and produce a full-color image.
White balance adjustment – Auto white balance (AWB) Adjusts color tones, ensuring whites appear natural regardless of the lightning. AWB removes unwanted color casts, adapting to different light sources (like sunlight or indoor lightning) for realistic colors.
Color correction & enhancement – The camera fine-tunes colors, making them appear more vibrant and true-to-life.
Tone & contrast adjustment – Brightness, shadows, highlights and contrast are fine-tuned, these adjustments add depth and dimension to the image, ensuring that it looks dynamic and balanced
Noise filtering & sharpness – The camera reduces unwanted visual artifacts, or “noise”, that can appear as grainy texture, especially in low-light conditions.

Before and after examples

From Basic to Fine tuning

More about it

The science of image quality

Image Quality Lab

An Image Quality (IQ) Lab is a specialized environment designed to assess and test the performance of camera systems against objective quality requirements. It ensures that cameras meet specific standards for image clarity, color accuracy, resolution, dynamic range, and overall visual performance. The IQ lab conducts controlled experiments to measure how well a camera can capture images under various conditions, making it essential for developing and fine-tuning camera technology across industries.

Our IQ Lab Equipment

Our state-of-the-art Image Quality Lab is equipped with advanced tools to accurately test and calibrate camera systems. This includes the X-Rite Spectra Box for precise color calibration, the Celeb 400 light sources to simulate various lighting conditions, and a wide range of IQ charts for detailed performance analysis. Additionally, we use 3D scenes for testing filters and optical performance, ensuring thorough evaluation of every aspect of image quality.

Automation for Accurate Reporting

We utilize automated procedures to generate both objective and subjective reports, streamlining the testing process and ensuring consistency in results. This allows for efficient analysis of camera performance, providing valuable insights to enhance image quality. Whether measuring technical specifications or evaluating visual perception, our automated system guarantees comprehensive and reliable assessments to meet every camera’s quality requirements.

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We collaborated with Software Supreme to help integrate our camera systems with NVIDIA Jetson AGX Xavier and refine image signal processor (ISP) functionalities. Their team, starting with one principal and later expanding to 3-4 members, adeptly debugged and enhanced drivers, and migrated algorithms from MATLAB to the NVIDIA platform. We are pleased with their dedication and ability to meet tight deadlines, and the project has been ongoing since December 2019. We have no significant areas for improvement.

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