Data binning is a data pre-processing technique used to reduce the effects of minor observation errors. The original data values which fall in a given small interval, a bin, are replaced by a value representative of that interval, often the central value. It is a form of quantization

Quantization (signal processing)

Quantization, in mathematics and digital signal processing, is the process of mapping a large set of input values to a smaller set – such as rounding values to some unit of precision. A device or algorithmic function that performs quantization is called a quantizer. The error introduced by...

.

Introduction

In the context of image processing, binning is the procedure of combining a cluster of pixels

Pixel

In digital imaging, a pixel, or pel, is a single point in a raster image, or the smallest addressable screen element in a display device; it is the smallest unit of picture that can be represented or controlled....

 into a single pixel. As such, in 2x2 binning, an array of 4 pixels becomes a single larger pixel, reducing the overall number of pixels.
This aggregation reduces the impact of read noise on the processed image at the cost of a lower resolution.

Example

For example, data binning may be used when small instrumental shifts in the spectral dimension from MS

Mass spectrum

A mass spectrum is an intensity vs. m/z plot representing a chemical analysis. Hence, the mass spectrum of a sample is a pattern representing the distribution of ions by mass in a sample. It is a histogram usually acquired using an instrument called a mass spectrometer...

 or NMR

Nuclear magnetic resonance

Nuclear magnetic resonance is a physical phenomenon in which magnetic nuclei in a magnetic field absorb and re-emit electromagnetic radiation...

 experiments will be falsely interpreted as representing different components, when a collection of data profiles is subjected to pattern recognition

Pattern recognition

In machine learning, pattern recognition is the assignment of some sort of output value to a given input value , according to some specific algorithm. An example of pattern recognition is classification, which attempts to assign each input value to one of a given set of classes...

 analysis. A straightforward way to cope with this problem is by using binning techniques in which the spectrum is reduced in resolution to a sufficient degree to ensure that a given peak remains in its bin despite small spectral shifts between analyses. For example, in NMR the chemical shift

Chemical shift

In nuclear magnetic resonance spectroscopy, the chemical shift is the resonant frequency of a nucleus relative to a standard. Often the position and number of chemical shifts are diagnostic of the structure of a molecule...

 axis may be discretized and coarsely binned, and in MS the spectral accuracies may be rounded to integer atomic mass unit

Atomic mass unit

The unified atomic mass unit or dalton is a unit that is used for indicating mass on an atomic or molecular scale. It is defined as one twelfth of the rest mass of an unbound neutral atom of carbon-12 in its nuclear and electronic ground state, and has a value of...

 values.

Also, several digital camera systems incorporate an automatic pixel binning function to allow the display of a brighter preview image.

See also

• Histogram
  Histogram
  In statistics, a histogram is a graphical representation showing a visual impression of the distribution of data. It is an estimate of the probability distribution of a continuous variable and was first introduced by Karl Pearson...
  
  
• Grouped data
  Grouped data
  Grouped data is a statistical term used in data analysis. A raw dataset can be organized by constructing a table showing the frequency distribution of the variable...
  
  
• Level of measurement
  Level of measurement
  The "levels of measurement", or scales of measure are expressions that typically refer to the theory of scale types developed by the psychologist Stanley Smith Stevens. Stevens proposed his theory in a 1946 Science article titled "On the theory of scales of measurement"...
  
  
• Quantization (signal processing)
  Quantization (signal processing)
  Quantization, in mathematics and digital signal processing, is the process of mapping a large set of input values to a smaller set – such as rounding values to some unit of precision. A device or algorithmic function that performs quantization is called a quantizer. The error introduced by...
  
  
• Discretization of continuous features
  Discretization of continuous features
  In statistics and machine learning, discretization refers to the process of converting or partitioning continuous attributes, features or variables to discretized or nominal attributes/features/variables/intervals. This can be useful when creating probability mass functions – formally, in density...