Noise in digital photography is primarily caused by high ISO settings. When the ISO is increased to capture images in low-light conditions, the camera's sensor becomes more sensitive to light, which also amplifies the noise present in the image.

The median filter is a noise reduction technique that works by replacing the value of a pixel with the median value of its neighboring pixels. This helps to reduce noise while preserving edges and details in the image.

Gaussian blur is a noise reduction technique that applies a bell-shaped curve to the image, resulting in a smooth and gradual transition between pixels. This helps to reduce noise without introducing noticeable blur or loss of detail.

The bilateral filter is a noise reduction technique that combines the advantages of both the median filter and the Gaussian blur filter. It preserves fine details and edges in the image by considering the spatial relationship between pixels when calculating the new pixel values.

The unsharp mask filter is a noise reduction technique that sharpens edges in the image while simultaneously reducing noise. It does this by creating a slightly blurred version of the image and then subtracting it from the original image, resulting in enhanced edges and reduced noise.

The channel mixer is a noise reduction technique that allows you to adjust the individual color channels of an image. By reducing the noise in the specific color channels affected by noise, you can effectively remove color noise while preserving the overall color balance of the image.

It is generally recommended to apply noise reduction after making basic adjustments like exposure and white balance to the image. This ensures that the noise reduction is applied to the properly exposed and color-balanced image, resulting in more effective and accurate noise reduction.

To minimize the need for noise reduction in portrait photography, it is important to use a tripod to stabilize the camera, shoot in RAW format to capture more image data, and use a lower ISO setting to reduce noise. By following these practices, you can capture images with minimal noise, reducing the need for extensive noise reduction during post-processing.

Adobe Photoshop, Lightroom, and Capture One are popular software programs that offer a range of noise reduction tools and features specifically designed for portrait photography. These programs allow you to apply various noise reduction techniques, adjust noise reduction settings, and fine-tune the noise reduction process to achieve the desired results.

The primary goal of noise reduction in portrait photography is to reduce noise while preserving the overall image quality. Noise reduction techniques aim to eliminate unwanted noise artifacts without compromising the sharpness, detail, and color accuracy of the image. The goal is to achieve a balance between noise reduction and image quality.

The median filter is particularly effective in removing luminance noise, which is the random variation in brightness values across an image. It works by replacing each pixel with the median value of its neighboring pixels, effectively reducing noise while preserving edges and details.

The effect of noise reduction on the file size of an image depends on the specific noise reduction technique used. Some techniques, such as the median filter, may slightly increase the file size due to the addition of new pixel values. Other techniques, like Gaussian blur, may slightly decrease the file size by reducing the overall image detail. However, in general, noise reduction techniques have a minimal impact on the file size of an image.

The recommended noise reduction setting for portrait photography depends on the specific image and the level of noise present. There is no one-size-fits-all setting that works for all images. It is important to adjust the noise reduction settings based on the characteristics of the image, such as the ISO used, the lighting conditions, and the desired level of detail preservation.

Noise reduction can be applied to both RAW and JPEG images. RAW images typically offer more flexibility and control over noise reduction, as they contain more image data. However, JPEG images can also be processed with noise reduction techniques, although the results may be less optimal due to the lossy nature of the JPEG format.

Noise reduction can have a significant impact on the overall look and feel of a portrait image. It can improve the image quality and clarity by reducing noise artifacts, but it can also make the image look artificial and over-processed if applied excessively. Additionally, noise reduction can potentially reduce the sharpness and detail of the image, especially if strong noise reduction techniques are used.