[Video] Post-Processing Demo: Noise Reduction

Minimizing the grain for better-quality images.

I photograph a lot at night and, over time, I have had to learn ways to minimize the noise that comes as a result of shooting at high ISOs. Without this noise reduction, I would see a massive decrease in the quality of my images.

Noise in photography refers to the random variation of brightness or colour information in images, often noticeable as grain or speckling, especially in low-light conditions.

The example above is a noisy, unedited image from the Scottish Highlands.

Noise in photography occurs due to limitations in the way a camera sensor captures and processes light. These include:

• Insufficient Light: In low-light situations, the sensor struggles to receive enough photons (light particles).

• High ISO Settings: Raising the ISO amplifies the sensor’s sensitivity to light, which simultaneously boosts electronic noise from the sensor, resulting in grainier images.

• Small Sensor Size: Smaller sensors, such as those in smartphones or compact cameras, have smaller individual pixels, which collect less light.

• Long Exposure Times: During long exposures, the sensor is active for extended periods, increasing the likelihood of heat buildup. This introduces thermal noise, creating random bright pixels across the image.

• Electronic Interference: Imperfections in the camera’s circuitry or sensor can introduce noise into the captured image.

• Post-Processing Limits: In some cases, noise appears more noticeable after heavy processing, such as lifting shadows or recovering details from underexposed areas, as the software enhances both the image data and the underlying noise.

Therefore, noise reduction involves finding a balance between exposure settings, sensor quality, and post-processing techniques to ensure optimal image quality.

In this month’s exclusive content, I share the tools I use to reduce noise in post-processing.