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Automated Two-dimensional Spatiotemporal Analysis of Mobile Single-molecule FRET Probes

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Intensity mappings within the context of near-sensor image processing.

A Aström, R Forchheimer, P E Danielsson

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society

|February 16, 2008

Summary

Near-sensor image processing (NSIP) offers flexible intensity mapping via variable thresholds or delays. This approach efficiently performs adaptive mapping, including histogram equalization, enhancing sensor processing power.

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Area of Science:

Sensor technology
Image processing
Computational imaging

Background:

The original near-sensor image processing (NSIP) maps sensor element intensity to time, with threshold-crossing time inversely proportional to intensity.
Existing NSIP methods may require alternative intensity-time mappings for specific applications.

Discussion:

This study explores achieving alternative intensity-time mappings in NSIP by incorporating delays or adjusting threshold voltages.
Variable threshold voltage is identified as a more efficient method for linear mapping, optimizing sensor processing power utilization.

Key Insights:

Adaptive mapping, such as histogram equalization, can be performed with minimal computational overhead within the NSIP framework.
NSIP facilitates straightforward implementation of other histogram-based, data-dependent mappings.

Outlook:

Further research can explore advanced adaptive algorithms for NSIP.
The NSIP concept holds potential for real-time, on-chip image analysis and feature extraction.