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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.

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Understanding Spatial Noise and Its Reduction Methods Using Convolution

Suresh Madhu
by Suresh Madhu
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...
Sensor and ISPTechnology Deep Dive

A Deep Dive into Resolution from Sensor Standpoints

Prabu Kumar
by Prabu Kumar
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!...
Sensor and ISPTechnology Deep Dive

A Comprehensive Guide to Hyperspectral Imaging in Embedded Vision Applications

Prabu Kumar
by Prabu Kumar
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!...
Sensor and ISPTechnology Deep Dive

What is Color Accuracy? How to Measure Color Accuracy?

Prabu Kumar
by Prabu Kumar
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...
Technology Deep Dive

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

Prabu Kumar
by Prabu Kumar
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....
Technology Deep Dive

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

Prabu Kumar
by Prabu Kumar
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....
Sensor and ISPTechnology Deep Dive

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

Prabu Kumar
by Prabu Kumar
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....
Technology Deep Dive

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

Prabu Kumar
by Prabu Kumar
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....
OpticsTechnology Deep Dive

Optical Zoom vs. Digital Zoom in Embedded Vision Cameras

Prabu Kumar
by Prabu Kumar
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....
Sensor and ISPTechnology Deep Dive

What is Gamma Correction and Its Importance in Embedded Vision?

Prabu Kumar
by Prabu Kumar
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....