Some machine vision cameras—including models from Adimec—feature an Output Lookup Table (LUT). This tool allows for remapping the camera’s linear output in different ways, though LUTs are commonly associated with compensating for non-linear screen emissions.

Beyond standard uses, a LUT can enhance specific image areas. For instance, contrast enhancement through compression of blacks while boosting other parts simultaneously is achievable via these tables. White compression techniques find frequent application in human-centric viewing scenarios such as outdoor surveillance and radiology.

A less recognized function involves data compression without information loss—like reducing bit depth from 10 to 8 bits—to support faster frame rates, which remains critical despite advancements like CoaXPress offering high-speed capabilities with high-resolution cameras. However, Camera Link persists due to existing infrastructure in many systems.

If utilizing faster sensor timing via Camera Link is desired alongside standard operations, employing LUTs for data compression presents one viable solution worth exploring.

Modern sensors, particularly those based on advanced CMOS technology, boast a wide dynamic range—often exceeding 60 dB. Transmitting linear video losslessly typically requires 10-bit precision (2^10 values logarithmically representing this range). Yet Camera Link’s highest configuration (CL-10tap) restricts data to only eight bits.

The raw pixel signals from image sensors quantify detected photons, affected by two primary noise types:

(1) Readout noise, independent of individual pixels; and

(2) Shot noise, proportional to the square root of light intensity per pixel.

Crucially, noise magnitude varies with signal level—increasing as brightness rises. Consequently, bit allocation for quantization ideally matches this variability: finer granularity suffices where signals are weak (noise-prone), while stronger signals tolerate larger intervals between quantization steps due to higher inherent noise masking such detail.

By applying non-linear compression prior to eight-bit quantization, the effective signal-to-noise performance becomes uniform across all levels. This transformation preserves the full 10-bit information within compacted eight-bit packets via a custom LUT at transmission endpoints and restoration upon reception—achieving complete data integrity despite reduced bandwidth demands.

Further acceleration can be attained through burst mode operation.

Last Updated: 2025-09-04 19:09:54