Zernike polynomials


In mathematics, the Zernike polynomials are a sequence of polynomials that are orthogonal on the unit disk. Named after optical physicist Frits Zernike, laureate of the 1953 Nobel Prize in Physics and the inventor of phase-contrast microscopy, they play important roles in various optics branches such as beam optics and imaging.[1][2]

The first 21 Zernike polynomials, ordered vertically by radial degree and horizontally by azimuthal degree



There are even and odd Zernike polynomials. The even Zernike polynomials are defined as


(even function over the azimuthal angle  ), and the odd Zernike polynomials are defined as


(odd function over the azimuthal angle  ) where m and n are nonnegative integers with n ≥ m ≥ 0 (m = 0 for spherical Zernike polynomials),   is the azimuthal angle, ρ is the radial distance  , and   are the radial polynomials defined below. Zernike polynomials have the property of being limited to a range of −1 to +1, i.e.  . The radial polynomials   are defined as


for an even number of nm, while it is 0 for an odd number of nm. A special value is


Other representations


Rewriting the ratios of factorials in the radial part as products of binomials shows that the coefficients are integer numbers:


A notation as terminating Gaussian hypergeometric functions is useful to reveal recurrences, to demonstrate that they are special cases of Jacobi polynomials, to write down the differential equations, etc.:


for nm even.

The inverse relation expands   for fixed   into  


with rational coefficients  [3]


for even  .

The factor   in the radial polynomial   may be expanded in a Bernstein basis of   for even   or   times a function of   for odd   in the range  . The radial polynomial may therefore be expressed by a finite number of Bernstein Polynomials with rational coefficients:


Noll's sequential indices


Applications often involve linear algebra, where an integral over a product of Zernike polynomials and some other factor builds a matrix elements. To enumerate the rows and columns of these matrices by a single index, a conventional mapping of the two indices n and l to a single index j has been introduced by Noll.[4] The table of this association   starts as follows (sequence A176988 in the OEIS).  

n,l 0,0 1,1 1,−1 2,0 2,−2 2,2 3,−1 3,1 3,−3 3,3
j 1 2 3 4 5 6 7 8 9 10
n,l 4,0 4,2 4,−2 4,4 4,−4 5,1 5,−1 5,3 5,−3 5,5
j 11 12 13 14 15 16 17 18 19 20

The rule is the following.

  • The even Zernike polynomials Z (with even azimuthal parts  , where   as   is a positive number) obtain even indices j.
  • The odd Z obtains (with odd azimuthal parts  , where   as   is a negative number) odd indices j.
  • Within a given n, a lower   results in a lower j.

OSA/ANSI standard indices


OSA [5] and ANSI single-index Zernike polynomials using:

n,l 0,0 1,−1 1,1 2,−2 2,0 2,2 3,−3 3,−1 3,1 3,3
j 0 1 2 3 4 5 6 7 8 9
n,l 4,−4 4,−2 4,0 4,2 4,4 5,−5 5,−3 5,−1 5,1 5,3
j 10 11 12 13 14 15 16 17 18 19

Fringe/University of Arizona indices


The Fringe indexing scheme is used in commercial optical design software and optical testing in, e.g., photolithography.[6][7]


where   is the sign or signum function. The first 20 fringe numbers are listed below.

n,l 0,0 1,1 1,−1 2,0 2,2 2,−2 3,1 3,−1 4,0 3,3
j 1 2 3 4 5 6 7 8 9 10
n,l 3,−3 4,2 4,−2 5,1 5,−1 6,0 4,4 4,−4 5,3 5,−3
j 11 12 13 14 15 16 17 18 19 20

Wyant indices


James C. Wyant uses the "Fringe" indexing scheme except it starts at 0 instead of 1 (subtract 1).[8] This method is commonly used including interferogram analysis software in Zygo interferometers and the open source software DFTFringe.

Rodrigues Formula


They satisfy the Rodrigues' formula


and can be related to the Jacobi polynomials as






The orthogonality in the radial part reads[9]




Orthogonality in the angular part is represented by the elementary


where   (sometimes called the Neumann factor because it frequently appears in conjunction with Bessel functions) is defined as 2 if   and 1 if  . The product of the angular and radial parts establishes the orthogonality of the Zernike functions with respect to both indices if integrated over the unit disk,


where   is the Jacobian of the circular coordinate system, and where   and   are both even.

Zernike transform


Any sufficiently smooth real-valued phase field over the unit disk   can be represented in terms of its Zernike coefficients (odd and even), just as periodic functions find an orthogonal representation with the Fourier series. We have


where the coefficients can be calculated using inner products. On the space of   functions on the unit disk, there is an inner product defined by


The Zernike coefficients can then be expressed as follows:


Alternatively, one can use the known values of phase function G on the circular grid to form a system of equations. The phase function is retrieved by the unknown-coefficient weighted product with (known values) of Zernike polynomial across the unit grid. Hence, coefficients can also be found by solving a linear system, for instance by matrix inversion. Fast algorithms to calculate the forward and inverse Zernike transform use symmetry properties of trigonometric functions, separability of radial and azimuthal parts of Zernike polynomials, and their rotational symmetries.



The reflections of trigonometric functions result that the parity with respect to reflection along the x axis is

  for l ≥ 0,
  for l < 0.

The π shifts of trigonometric functions result that the parity with respect to point reflection at the center of coordinates is


where   could as well be written   because   as even numbers are only cases to get non-vanishing Zernike polynomials. (If n is even then l is also even. If n is odd, then l is also odd.) This property is sometimes used to categorize Zernike polynomials into even and odd polynomials in terms of their angular dependence. (it is also possible to add another category with l = 0 since it has a special property of no angular dependence.)

  • Angularly even Zernike polynomials: Zernike polynomials with even l so that  
  • Angularly odd Zernike polynomials: Zernike polynomials with odd l so that  

The radial polynomials are also either even or odd, depending on order n or m:


These equalities are easily seen since   with an odd (even) m contains only odd (even) powers to ρ (see examples of   below).

The periodicity of the trigonometric functions results in invariance if rotated by multiples of   radian around the center:


Recurrence relations


The Zernike polynomials satisfy the following recurrence relation which depends neither on the degree nor on the azimuthal order of the radial polynomials:[10]


From the definition of   it can be seen that   and  . The following three-term recurrence relation[11] then allows to calculate all other  :


The above relation is especially useful since the derivative of   can be calculated from two radial Zernike polynomials of adjacent degree:[11]


The differential equation of the Gaussian Hypergeometric Function is equivalent to




Radial polynomials


The first few radial polynomials are:


Zernike polynomials


The first few Zernike modes, at various indices, are shown below. They are normalized such that:  , which is equivalent to  .

( )
( )
( )
( )
( )
( )
  Classical name
  00 01 00 01 0 00   Piston (see, Wigner semicircle distribution)
  01 03 02 03 1 −1   Tilt (Y-Tilt, vertical tilt)
  02 02 01 02 1 +1   Tilt (X-Tilt, horizontal tilt)
  03 05 05 06 2 −2   Oblique astigmatism
  04 04 03 04 2 00   Defocus (longitudinal position)
  05 06 04 05 2 +2   Vertical astigmatism
  06 09 10 11 3 −3   Vertical trefoil
  07 07 07 08 3 −1   Vertical coma
  08 08 06 07 3 +1   Horizontal coma
  09 10 09 10 3 +3   Oblique trefoil
  10 15 17 18 4 −4   Oblique quadrafoil
  11 13 12 13 4 −2   Oblique secondary astigmatism
  12 11 08 09 4 00   Primary spherical
  13 12 11 12 4 +2   Vertical secondary astigmatism
  14 14 16 17 4 +4   Vertical quadrafoil


Result of the first 21 Zernike polynomials (as above) introduced as aberrations on a flat-top beam. The beam is imaged by a lens, effecting a Fourier transform, whose intensity is represented in this picture

The functions are a basis defined over the circular support area, typically the pupil planes in classical optical imaging at visible and infrared wavelengths through systems of lenses and mirrors of finite diameter. Their advantages are the simple analytical properties inherited from the simplicity of the radial functions and the factorization in radial and azimuthal functions; this leads, for example, to closed-form expressions of the two-dimensional Fourier transform in terms of Bessel functions.[12][13] Their disadvantage, in particular if high n are involved, is the unequal distribution of nodal lines over the unit disk, which introduces ringing effects near the perimeter  , which often leads attempts to define other orthogonal functions over the circular disk.[14][15][16]

In precision optical manufacturing, Zernike polynomials are used to characterize higher-order errors observed in interferometric analyses. In wavefront slope sensors like the Shack-Hartmann, Zernike coefficients of the wavefront can be obtained by fitting measured slopes with Zernike polynomial derivatives averaged over the sampling subapertures.[17] In optometry and ophthalmology, Zernike polynomials are used to describe wavefront aberrations of the cornea or lens from an ideal spherical shape, which result in refraction errors. They are also commonly used in adaptive optics, where they can be used to characterize atmospheric distortion. Obvious applications for this are IR or visual astronomy and satellite imagery.

Another application of the Zernike polynomials is found in the Extended Nijboer–Zernike theory of diffraction and aberrations.

Zernike polynomials are widely used as basis functions of image moments. Since Zernike polynomials are orthogonal to each other, Zernike moments can represent properties of an image with no redundancy or overlap of information between the moments. Although Zernike moments are significantly dependent on the scaling and the translation of the object in a region of interest (ROI), their magnitudes are independent of the rotation angle of the object.[18] Thus, they can be utilized to extract features from images that describe the shape characteristics of an object. For instance, Zernike moments are utilized as shape descriptors to classify benign and malignant breast masses[19] or the surface of vibrating disks.[20] Zernike Moments also have been used to quantify shape of osteosarcoma cancer cell lines in single cell level.[21] Moreover, Zernike Moments have been used for early detection of Alzheimer's disease by extracting discriminative information from the MR images of Alzheimer's disease, Mild cognitive impairment, and Healthy groups.[22]

Higher dimensions


The concept translates to higher dimensions D if multinomials   in Cartesian coordinates are converted to hyperspherical coordinates,  , multiplied by a product of Jacobi polynomials of the angular variables. In   dimensions, the angular variables are spherical harmonics, for example. Linear combinations of the powers   define an orthogonal basis   satisfying


(Note that a factor   is absorbed in the definition of R here, whereas in   the normalization is chosen slightly differently. This is largely a matter of taste, depending on whether one wishes to maintain an integer set of coefficients or prefers tighter formulas if the orthogonalization is involved.) The explicit representation is[3]


for even  , else identical to zero.

See also



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  2. ^ Born, Max & Wolf, Emil (1999). Principles of Optics: Electromagnetic Theory of Propagation, Interference and Diffraction of Light (7th ed.). Cambridge, UK: Cambridge University Press. p. 986. ISBN 9780521642224. (see also at Google Books)
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  18. ^ Tahmasbi, A. (2010). An Effective Breast Mass Diagnosis System using Zernike Moments. 17th Iranian Conf. on Biomedical Engineering (ICBME'2010). Isfahan, Iran: IEEE. pp. 1–4. doi:10.1109/ICBME.2010.5704941.
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  • The Extended Nijboer-Zernike website
  • MATLAB code for fast calculation of Zernike moments
  • Python/NumPy library for calculating Zernike polynomials
  • Zernike aberrations at Telescope Optics
  • Example: using WolframAlpha to plot Zernike Polynomials
  • orthopy, a Python package computing orthogonal polynomials (including Zernike polynomials)