Image noise is random variation of brightness or color information in images due to electronic noise produced by the sensor of a digital camera. It is the digital equivalent of film grain from the film era. It is one of the most discussed and most hated entity in digital camera world. Although it can be sometimes used creatively to add an old-fashioned, grainy look which is reminiscent of early film, for most it is undesirable entity in their photo.
Image noise appears as random speckles on an otherwise smooth surface and can significantly degrade image quality. It is almost like the background hiss you hear when you crank up your audio system. Noise increases with the sensitivity setting in the camera, length of the exposure, temperature, and most importantly different camera models. Noise has no relation to the lens used, even though I have seen plenty of lens reviewers cursing the lens for creating noisy picture 😉
Noise is composed of two elements: Luminance & Chroma. Luminance noise is due to variation of brightness information whereas Chroma noise or color noise is due to variation of color information. The relative amount of Chroma and Luminance noise can vary significantly from one camera model to another. Chroma noise is usually more unnatural in appearance and can render images unusable if not kept under control.
In a camera, ISO setting is a standard which describes its absolute sensitivity to light. ISO settings are usually listed as factors of 2, such as ISO 50, ISO 100 and ISO 200 and higher numbers represent greater sensitivity. ISO is accomplished by amplifying the image signal in the camera, however this also amplifies noise and so higher ISO speeds will produce progressively more noise.
Digital cameras produce three common types of noises:
- Random noise
- Fixed pattern noise
- Banding noise
Random noise is characterized by intensity and color fluctuations above and below the actual image intensity. There will always be some random noise at any exposure length and it is most influenced by ISO speed. The pattern of random noise changes even if the exposure settings are identical. Random noise is usually much more difficult to remove without degrading the image and it is the commonest type of noise people see in their photo.
Fixed pattern noise also called hot pixels. Fixed pattern noise generally appears in very long exposures and is exacerbated by higher temperatures. Fixed pattern noise is unique in that it will show almost the same distribution of hot pixels if taken under the same conditions. Most cameras have settings to reduce this type of noise for long exposure. It tries to look for these hot pixel pattern and it can subtract this noise away to reveal the true image. That is why it is rarely seen type of noise.
Banding noise is highly camera-dependent, and is a type noise which is introduced by the camera when it reads data from the digital sensor. Banding noise is most visible at high ISO speeds and in the shadows, or when an image has been excessively brightened. Canon EOS 5D Mark II had a similar problem of banding noise with earlier firmware which was corrected after the upgrade (http://www.canon-europe.com/Support/Consumer_Products/products/cameras/Digital_SLR/EOS_5D_Mark_II.aspx?type=important&faqtcmuri=tcm:13-618473)
Noise not only changes depending on exposure setting and camera model, but it can also vary within an individual image. For digital cameras, darker regions will contain more noise than the brighter regions. Some degree of noise is always present in any electronic device that transmits or receives a signal. Signal to noise ratio is the important factor to look for.
Is Image noise all that bad? Apparently not. Most people look for noise by viewing their files at 100% on screen. This is a false comparison which heavily favors the noise performance of the lower resolution file. The larger file appears noisier. The higher resolution file has actually been blown up to a larger size in such comparisons.
To do a real comparison you need to consider what the two files look like when they are enlarged to the same physical size. That’s pretty easy to do. Simply print out a print of the same size from each camera. The apparent noise advantage of the less dense file typically disappears because it was an illusion. Even in print if you notice noise then you need to treat it.
Noise becomes less pronounced as the tones become brighter. Brighter regions have a stronger signal due to more light, resulting in a higher overall Signal to noise ratio. This means that images which are underexposed will have more visible noise — even if you brighten them up to a more natural level afterwards in post processing. Slightly overexposed (not overly blown out) images will have less noise and can actually be advantageous, assuming that you can darken them later. Post processing an under exposed photo and trying to correct it will introduce quite an amount of noise. This is the reason exposing it right in the camera is much more important if you want to reduce noise in your picture. Low ISO setting, better camera models and perfectly exposed or slightly over exposed picture are the key ingredient to reduce noise in your image.
Even though noise can be reduced in post processing, computers have a difficult time discerning random noise from fine texture patterns. Noise reduction software can be used to selectively reduce both chroma and luminance noise. Programs such as Lightroom, Topaz Denoise and Noise Ninja are remarkably good at reducing noise while still retaining actual image information. Be aware that if you try to completely eliminate luminance noise from the image, it can result in unnatural or “plasticy” looking images.