Sensor and ISP Archives - e-con Systems

What are the 7 Fundamental Calibration Blocks of an ISP – and how do they work together?

Arun AsokanOctober 7, 20260

An imaging system consists of three main parts – a sensor to collect light, a lens to direct the light onto the sensor and an ISP to process the collected light as an image, just like how we, as humans, see it. However, an image sensor does not see a...

How e-con Systems Solves Motion and Lighting Challenges in High-Speed Imaging

Vinoth RajagopalanOctober 5, 20260

Capturing fast-moving objects requires both precise image capture and controlled illumination. Fast-moving objects can introduce motion-related distortion, while the short exposure times used to freeze motion can reduce the light reaching the sensor. A global shutter camera addresses motion-related distortion by capturing the entire frame simultaneously, making it suitable for...

How the Lack of Black Level Correction Can Affect Image Quality

Prabu KumarJuly 15, 20260

The first blog in this series covered what Black Level Correction (BLC) is, the physics behind dark current and the black level offset, how that offset is measured, why sensors add a deliberate pedestal before the ADC, and how BLC interacts with each stage of the ISP pipeline from lens...

Black Level Correction in Image Sensors: What It Is and Why It Matters

Prabu KumarJuly 15, 20260

Black Level Correction (BLC) is a vital stage in the Image Signal Processing (ISP) pipeline. It is one of the components of the camera tuning process, and is usually performed after Dead Pixel Correction. BLC’s primary purpose is to remove sensor-generated offsets and noise present even without incoming light. In...

Sony IMX678 vs IMX715 vs IMX415: Which Sony STARVIS Sensor Does Your Vision System Need?

Prabu KumarMay 6, 20260

Sony’s IMX415, IMX715, and IMX678 CMOS image sensors represent successive generations in Sony’s imaging portfolio. All three sensors deliver 4K Ultra-HD (3840 × 2160) resolution but differ significantly in pixel architecture, sensitivity, and imaging performance. These sensors are widely used in industrial inspection, smart surveillance, and factory automation, where imaging

What is a spatial filter, and how does it enhance Depth Quality in ToF Cameras?

Prabu KumarApril 2, 20260

Prabu KumarPrabu is the Chief Technology Officer and Head of Camera Products at e-con Systems, and comes with a rich experience of more than 15 years in the embedded vision space. He brings to the table a deep knowledge in USB cameras, embedded vision cameras, vision algorithms and FPGAs. He...

Sony IMX412 vs Sony IMX676: A detailed comparison of Sony sensors for Embedded Vision Solutions

Prabu KumarApril 7, 20260

Sony's image sensors have undergone various generations of architectures, each of which has been designed to address certain image-related issues in embedded systems. Among Sony's high-resolution image sensors, the Sony IMX676 and Sony IMX412 deliver advanced capabilities such as high-speed imaging, superior low-light sensitivity, enhanced dynamic range, and improved near-infrared

Clear HDR vs DOL HDR: Which HDR Technology is Right for Your Application?

Prabu KumarFebruary 19, 20260

Embedded vision applications require the camera image sensor to capture a clear image under challenging illumination conditions, with no motion artifacts. The Sony STARVIS 2 image sensor family will meet this requirement by supporting advanced HDR modes, including clear HDR and DOL HDR, enabling high-end embedded vision cameras to deliver

Sony Pregius IMX264 vs. IMX568: A Detailed Sensor Comparison Guide

Prabu KumarJanuary 13, 20260

IMX264 and IMX568 both belong to the Sony Pregius family of image sensors, which feature global-shutter pixels. Both sensors are renowned for their sensitivity, low noise, and distortion-free imaging, and are well-suited to high-speed vision applications, especially those requiring light sensitivity. While both sensors belong to the same Pregius family,

What is a dust denoising filter in TOF camera, and how does it remove noise artifacts in vision systems?

Prabu KumarMarch 3, 20260

Time-of-Flight (ToF) cameras with IR sensors are susceptible to performance variations caused by environmental dust. This dust can create 'dust noise' in the output depth map, directly impacting camera accuracy and, consequently, the reliability of critical embedded vision applications.