In-camera noise reduction is a technique used to reduce the amount of noise in images captured in low-light conditions. Noise is a grainy or speckled appearance that can occur in images due to high ISO settings or poor lighting conditions.

In-camera noise reduction typically reduces both luminance noise (which affects the brightness of pixels) and chrominance noise (which affects the color of pixels).

In-camera noise reduction works by using a noise-reduction algorithm to analyze the image and identify areas of noise. The algorithm then applies various techniques to reduce the noise, such as smoothing the image or removing individual noisy pixels.

In-camera noise reduction can potentially lead to reduced image sharpness, increased image blur, and loss of fine detail. This is because the noise-reduction algorithm may smooth over details in the image in an attempt to remove noise.

In-camera noise reduction is generally recommended to be used when shooting in low-light conditions, with a high ISO setting, or with a long exposure time. These conditions are more likely to produce images with noise, which can be reduced by using in-camera noise reduction.

In-camera noise reduction can be applied to images after they have been captured using photo editing software. However, the results may not be as good as if the noise reduction had been applied during the shooting process.

Most major camera manufacturers, including Canon, Nikon, Sony, and others, offer in-camera noise reduction features in their cameras.

In-camera noise reduction is typically most effective at ISO settings between 800 and 1600. At lower ISO settings, there is less noise to reduce, while at higher ISO settings, the noise may be too severe for the noise-reduction algorithm to handle effectively.

In-camera noise reduction cannot completely eliminate noise from an image. It can only reduce the amount of noise, but some noise may still be visible in the image.

In-camera noise reduction is typically more effective than post-processing noise reduction because it is applied to the raw image data before any processing or compression is applied. Post-processing noise reduction, on the other hand, is applied to the final image, which may have already lost some detail due to processing and compression.

In-camera noise reduction does not typically affect the file size of images. This is because the noise-reduction algorithm is applied to the raw image data, which is then compressed using the same compression algorithm that would be used if noise reduction were not applied.

In-camera noise reduction can be used to reduce noise in videos, although it is not as common as noise reduction for still images. Some cameras offer video noise reduction features that can be applied during recording or post-processing.

Gaussian blur is not typically used as an in-camera noise reduction algorithm because it can lead to excessive image smoothing. Median filter, wavelet transform, and bilateral filter are all common types of in-camera noise reduction algorithms.

Wavelet transform is a powerful noise-reduction algorithm that offers several advantages for in-camera noise reduction. It preserves image sharpness, reduces noise in both luminance and chrominance channels, and is computationally efficient, making it suitable for real-time noise reduction in cameras.

Bilateral filter is generally effective at reducing noise in low-light conditions. It is the other options that are potential drawbacks of using a bilateral filter for in-camera noise reduction.