Technology Deep Dive

Do a deep dive into various camera technologies and understand how they enhance the performance of camera-based devices and help machines see better.

Suresh Madhu

Suresh Madhu is the product marketing manager with 16+ years of experience in embedded product design, technical architecture, SOM product design, camera solutions, and product development. He has played an integral part in helping many customers build their products by integrating the right vision technology into them.

Understanding Spatial Noise and Its Reduction Methods Using Convolution

Suresh MadhuJune 24, 20240

Convolution is a mathematical operation used in image processing to apply filters to images. These filters are used for spatial noise reduction in images with variations or irregularities in the pixel values that are unrelated to the actual features of the scene being captured. This blog delves into different filtering

A Deep Dive into Resolution from Sensor Standpoints

Prabu KumarDecember 3, 20240

In this blog, we're diving deep into sensor resolution and its impact on camera performance. Understanding sensor resolution is key to choosing the right camera for your needs. Keep reading for insights that will empower you on your next camera purchase!

A Comprehensive Guide to Hyperspectral Imaging in Embedded Vision Applications

Prabu KumarMay 10, 20240

Hyperspectral imaging lets cameras see beyond human vision. It offers a high spectral resolution by capturing data in large numbers of spectral bands. Explore the technical aspects of hyperspectral imaging and discover its applications in agriculture, environment, medicine, and other embedded vision applications!

What is Color Accuracy? How to Measure Color Accuracy?

Prabu KumarMay 2, 20240

Precisely capturing and reproducing colors of the outside world is essential for error-free image analysis. Cameras with high color accuracy prove beneficial in producing realistic images in various fields like surveillance and medical diagnosis cameras. This is a comprehensive blog on color accuracy, the measurement of color accuracy, and the

A Deep Dive into Types of Camera Noise, and Their Impact on Image Quality

Prabu KumarApril 23, 20240

Managing and mitigating camera noise can be a make-or-break moment. It often manifests as random pixel variations or color artifacts and degrades image quality. Find out the origins of camera noise, the different types, the practical impact, and finally - how to overcome.

A Comprehensive Study: MJPEG and H.264 Compression in Embedded Vision

Prabu KumarMarch 13, 20240

Many differences exist between MJPEG and H.264 video compression formats. MJPEG offers simplicity and high image quality, while H.264 takes efficiency to the next level. Get expert insights on their critical applications and considerations.

What is Signal-to-Noise Ratio (SNR)? Why is SNR important in embedded cameras?

Prabu KumarOctober 8, 20240

Signal-to-Noise Ratio (SNR) measures the strength of the desired signal relative to the background noise. Demystify how SNR is calculated and develop an understanding of the practical steps to improve SNR.

A Comprehensive Study: H.264 vs H.265 Compression in Embedded Vision

Prabu KumarMar 7, 20240

The choice between H.264 and H.265 video compression standards is crucial. One is known for its wide compatibility and performance, while the other doubles down on compression efficiency. Unearth a full comparison between these two standards.

Optical Zoom vs. Digital Zoom in Embedded Vision Cameras

Prabu KumarNovember 8, 20240

There are two major approaches to camera-related magnification - optical zoom and digital zoom. One relies on manual adjustments while the other leverages software algorithms. Explore the differences, advantages, and limitations of both these approaches.

What is Gamma Correction and Its Importance in Embedded Vision?

Prabu KumarNovember 6, 20240

Gamma correction play a key role in ensuring that images appear correctly in the camera, taking into account the non-linear perception of brightness. Get to know how gamma correction works, why it's important for embedded vision systems and some of the challenges that need to be overcome.