你可以看看噪聲的說明，關于固定格式噪聲，熱噪聲等等的公式，自然知道它的分布規(guī)律和模型！
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u+~) 大部分的噪聲最后反應都在圖像上，這是從圖像上我們常規(guī)的總結圖像噪聲的一些資料：
3eUi9_s+ /we]i1-9 Gaussian noise
M i.#x_ fM.#FT?? Main article: Gaussian noise
/`m* PgJ Principal sources of Gaussian noise in digital images arise during acquisition e.g. sensor noise caused by poor illumination and/or high temperature, and/or transmission e.g. electronic circuit noise.[2]
|sGJum&= A typical model of image noise is Gaussian, additive, independent at each pixel, and independent of the signal intensity, caused primarily by Johnson–Nyquist noise (thermal noise), including that which comes from the reset noise of capacitors ("kTC noise").[3] Amplifier noise is a major part of the "read noise" of an image sensor, that is, of the constant noise level in dark areas of the image.[4] In color cameras where more amplification is used in the blue color channel than in the green or red channel, there can be more noise in the blue channel.[5] At higher exposures, however, image sensor noise is dominated by shot noise, which is not Gaussian and not independent of signal intensity.
.i;.5)shsu CbZ;gjgY* Salt-and-pepper noise
;MQl.?vj "}X+vd`` Main article: Salt and pepper noise
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'-"[>`[q Ry +?#P+ Image with salt and pepper noiseFat-tail distributed or "impulsive" noise is sometimes called salt-and-pepper noise or spike noise.[6] An image containing salt-and-pepper noise will have dark pixels in bright regions and bright pixels in dark regions.[7] This type of noise can be caused byanalog-to-digital converter errors, bit errors in transmission, etc.[8][9] It can be mostly eliminated by using dark frame subtraction and interpolating around dark/bright pixels.
g%J\YRo Dead pixels in an LCD monitor produce a similar, but non-random, display.[10]
E:qh}wY Wrp~OF0k Shot noise
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{H3r&/S The dominant noise in the lighter parts of an image from an image sensor is typically that caused by statistical quantum fluctuations, that is, variation in the number of photons sensed at a given exposure level. This noise is known as photon shot noise.[5] Shot noise has a root-mean-square value proportional to the square root of the image intensity, and the noises at different pixels are independent of one another. Shot noise follows a Poisson distribution, which is usually not very different from Gaussian.
>~ *wPoW In addition to photon shot noise, there can be additional shot noise from the dark leakage current in the image sensor; this noise is sometimes known as "dark shot noise"[5] or "dark-current shot noise".[11] Dark current is greatest at "hot pixels" within the image sensor. The variable dark charge of normal and hot pixels can be subtracted off (using "dark frame subtraction"), leaving only the shot noise, or random component, of the leakage.[12][13]If dark-frame subtraction is not done, or if the exposure time is long enough that the hot pixel charge exceeds the linear charge capacity, the noise will be more than just shot noise, and hot pixels appear as salt-and-pepper noise.
>$ZhhM/} J T'6`A<`3 S:{xx`6K Quantization noise (uniform noise)
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,hf W2} The noise caused by quantizing the pixels of a sensed image to a number of discrete levels is known as quantization noise. It has an approximately uniform distribution. Though it can be signal dependent, it will be signal independent if other noise sources are big enough to cause dithering, or if dithering is explicitly applied.[9]
(c0L@ 8L E,d<F{=8,o w<~[ad} Film grain[edit]
2=?3MXcjy o_}?aI~H The grain of photographic film is a signal-dependent noise, with similar statistical distribution to shot noise.[14] If film grains are uniformly distributed (equal number per area), and if each grain has an equal and independent probability of developing to a dark silver grain after absorbing photons, then the number of such dark grains in an area will be random with a binomial distribution. In areas where the probability is low, this distribution will be close to the classic Poisson distribution of shot noise. A simple Gaussian distribution is often used as an adequately accurate model.[9]
%<^^ Mw Film grain is usually regarded as a nearly isotropic (non-oriented) noise source. Its effect is made worse by the distribution of silver halide grains in the film also being random.[15]
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