SNR calculation from 8-bit camera images: fix negative signed values

Min, max and mean come out negative on a mono 8-bit camera, and the SNR expression you were about to run, 20·log10((max - min)/σ), looks untrustworthy as a result. The camera is almost never at fault. Negative statistics mean your code reads the buffer as signed while the camera delivered unsigned data, so every pixel at or above half scale wraps into negative numbers. The fix comes in two parts: get honest unsigned counts into your statistics, then compute SNR the way camera data sheets do, as mean divided by standard deviation on a flat grey patch. With a mean of 128 counts and σ of 3 counts, the correct answer is 20·log10(42.7) ≈ 32.6 dB, and the arithmetic below shows every step.

Why grey pixels go negative

A signed sample uses its top bit as the sign. Read an 8-bit byte as signed and the scale splits at 128: values 0-127 keep their value, and values 128-255 come out as value minus 256, that is -128 through -1. The same rule at 16 bits splits at 32,768. Nothing about the camera changed; only the interpretation of the bytes did.

Run the arithmetic on a flat target whose counts sit between 150 and 170. The honest minimum, maximum and mean are 150, 170 and 160. Read as signed bytes they become 150 - 256 = -106, 170 - 256 = -86 and 160 - 256 = -96: every statistic negative, and any logarithm of the mean fails outright. That is the exact symptom in front of you, and it is arithmetic, not hardware.

The wrap is not specific to imaging. Any signed container folds its top half negative, which is why integrators meet the same bug decoding PLC registers: values above 32,767 come out negative until the bytes are reinterpreted as unsigned, as this walkthrough of signed versus unsigned integer decoding above 32,767 shows. Cameras add one twist: the wrap often hides in a preview, because viewers clip or rescale either interpretation to fill the screen.

Two neighbours worth separating from signed data: an image that renders black or doubled usually has shifted data, with 10- or 12-bit values sitting in the wrong bit positions. That case is covered in why 10-bit PNG images look black in image viewers, why 12-bit camera images look black in a 16-bit preview and the underlying ADC bit depth versus pixel format explanation. Fix signs first, shifts second; the table below tells you which one you have.

Likely causes, in order of probability

1. Signed container, unsigned camera. Most acquisition libraries give their image object a fixed internal container at creation, and several use a signed 16-bit type whatever the camera sends, which is also why the array-conversion step offers only a signed 16-bit output. Test: read the element type of the array your conversion returns. Fix in the next section.
2. The camera's pixel format is not the one you assumed. A camera left in Mono 16 sends 2 bytes per pixel; statistics over half the buffer or over alternating bytes both give garbage. The delivered byte count must equal width × height × bytes per pixel: a 4000 × 3000 Mono 8 frame occupies 12 MB (4000 × 3000 × 1 byte), and the same frame in a 16-bit format occupies 24 MB. The general check is in buffer size checks before processing. Fix: set the format you want, or handle 2-byte samples end to end.
3. A conversion in the middle changed the type. Save-then-reload, or an intermediate preview step, can hand the statistics a signed copy while your grab code is correct. Test: dump the same ten pixels straight after acquisition and again right before the statistics, against a capped-lens dark frame. The pattern to follow is the converted image object pixel format check. Fix: convert explicitly, once, where you grab.
4. Signedness inside the maths rather than the buffer. Rare, but it happens: a cast sitting inside the statistics routine. Test: run min and max on a capped-lens dark frame at the point of the call; a negative minimum there means the container is still signed when the statistics run.

Fix the container type before the first grab

1. Set the camera's pixel format to Mono8, the value a GenICam camera exposes in its pixel-format feature, unless you specifically need deeper data for this decision.
2. Create the image object with an unsigned 8-bit type at creation time, before the first grab. The library default is where signed 16-bit containers sneak in.
3. Grab one frame of a uniform grey target and run minimum, maximum and mean. All three must be positive and at or below 255.
4. Save that frame in an ordinary 8-bit format as a second gate; a writer that accepts it confirms an 8-bit buffer.
5. Run the SNR maths on that container, with nothing between the grab and the statistics that can retype the data.

If the camera must stay in a 16-bit pixel format, create a 16-bit container of matching unsignedness and carry 2 bytes per pixel through every size check. The rule is the same one level deeper: container matches format.

Cast or shift a buffer you cannot re-create

Some stacks lock the container: the driver fills its own signed structure and hands you a view of it. Convert before the statistics, once and explicitly.

// generic pseudo-code, no library calls, types explicit
uint8[] px8 = reinterpret_as_u8(buffer)        // 8-bit data held in signed bytes: free view change
uint16  u16 = uint16(int16_value + 32768)      // unsigned 16-bit held in a signed container: shift up

An 8-bit value in signed bytes needs only a reinterpretation, with no per-pixel work. Unsigned 16-bit data in a signed container needs the +32,768 shift per sample, or an equivalent flip of the top bit. The full walk-through with a worked array is in I16 to U16 conversion: fix signed 16-bit camera data fast.

Prove the conversion on known input: point at the flat target and confirm the same patch reads minimum 150, maximum 170 and mean 160 after the cast. In a threaded pipeline, copy the pixels into your own buffer first, because a driver that reuses its buffers mid-read hands you torn frames; that failure mode is described in copying frame data out of the SDK buffer.

Measure SNR as mean over sigma

The (max - min)/σ expression compares the frame's total contrast with its noise, so it returns a different number for every scene and labels it the camera's. Data-sheet figures come from the EMVA 1288 method: illuminate uniformly, then read the mean signal and the noise standard deviation on the same patch. The honest camera number in decibels is:

A bound worth memorising: at 8 bits, the best possible reading at one grey level is a mean of 255 with σ of 1 count, 20 · log10(255) ≈ 48 dB. If your maths reports 60 dB from 8-bit data, the input is still wrong. No formula creates information the converter did not capture.

Checks before you trust the number

• Capped-lens dark frame first. Every value positive, mean at the camera's black level, σ of 1-3 counts typical for an 8-bit sensor at room temperature; quantization alone contributes one step over √12 ≈ 0.29 counts. A negative minimum here means the container is still signed.
• Uniform patch, not the whole frame. At least 100 × 100 pixels, centred, away from edges and shading. The patch's σ is the noise; the patch's mean is the signal.
• Exposure high enough that quantization is negligible. At σ = 3 counts, quantization contributes (0.29 / 3)² ≈ 0.9% of the noise variance. Below σ ≈ 1 count it dominates, and the 8-bit scale itself is the limit.
• Separate temporal from spatial noise. Grab 20 or more frames and take per-pixel σ across frames. If single-frame spatial σ is far larger, the extra is fixed-pattern noise (pixel-to-pixel response spread), which EMVA 1288 reports separately and a flat-field correction removes.
• Byte count on every run. Array length must equal width × height for Mono 8. Twice that means the pixel format moved under you.

Prevention: keep one format end to end

Pin the pixel format in the camera configuration and the container type at image creation, then leave nothing between grab and statistics that can retype the data. Re-run the dark and flat checks after any acquisition-stack update: container mismatches often arrive with a new driver rather than a code change, the same way a gray preview from a format mismatch does.

In a multi-camera cell, keep the chain boring: identical pixel formats on every camera, your own copy of every frame, and simple transport. Where several GigE cameras share one host, give each its own port: the MV-GE2002P is a dual-port PoE NIC built for exactly that, and the wider choice sits under frame grabbers with the accessories finder.

When the code is right and SNR is still too low

Light is the remaining lever. Photon arrivals follow Poisson statistics, so SNR grows with the square root of collected photons: each doubling of exposure, aperture or illumination buys about 3 dB (20 · log10(√2) ≈ 3.0 dB). Take the free decibels first — more light, longer exposure, wider aperture — then look at the sensor, where larger pixels or a higher full well collect more photons per pixel at the same optics.

Run the measurement on a mono sensor when you can. Without a colour filter array, every photon lands on the measurement and you read raw counts instead of demosaiced estimates. The MV-CS200-10UM pairs a 1-inch mono sensor with 20 MP resolution over USB3, a fit when the decision needs detail and photons together.

Browse area scan cameras through the camera finder, or start at the camera step of the configurator and add lens and light next. If a grab and its statistics still disagree after the checks above, send both through the contact page and we will read the buffer with you. The systems topic page collects the rest of these format and acquisition fixes.