Histogram Linearization Calculator

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Intensity Transformation Basics of Image Processing

✖Number of Intensity Levels is the total number of distinct intensity values an image can represent, determined by its bit depth.ⓘ Number of Intensity Levels [L]			+10% -10%
✖Digital Image Row is the row or small pixel that is present at the x-axis storing image information.ⓘ Digital Image Row [M]			+10% -10%
✖Digital Image Column is the column or small pixel that is present at the y-axis.ⓘ Digital Image Column [N]			+10% -10%
✖Number of Pixels with Intensity Ri is the number of pixels that have intensity Ri.ⓘ Number of Pixels with Intensity Ri [n_j]			+10% -10%

✖Discrete Form of Transformation is The transformation (mapping) in this equation is called a histogram equalization or histogram linearization transformation.ⓘ Histogram Linearization [s_k]

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Formula

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Histogram Linearization

Formula

s k = (\frac{L - 1}{M \cdot N} \cdot \sum (x, 0, L - 1, n j))

Example

43.71585 = (\frac{4 - 1}{9 \cdot 0.061} \cdot \sum (x, 0, 4 - 1, 2))

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Histogram Linearization Solution

STEP 0: Pre-Calculation Summary

Formula Used

Discrete Form of Transformation = ((Number of Intensity Levels-1)/(Digital Image Row*Digital Image Column)*sum(x,0,Number of Intensity Levels-1,Number of Pixels with Intensity Ri))
s_k = ((L-1)/(M*N)*sum(x,0,L-1,n_j))
This formula uses 1 Functions, 5 Variables

Functions Used

sum - Summation or sigma (∑) notation is a method used to write out a long sum in a concise way., sum(i, from, to, expr)

Variables Used

Discrete Form of Transformation - Discrete Form of Transformation is The transformation (mapping) in this equation is called a histogram equalization or histogram linearization transformation.
Number of Intensity Levels - Number of Intensity Levels is the total number of distinct intensity values an image can represent, determined by its bit depth.
Digital Image Row - Digital Image Row is the row or small pixel that is present at the x-axis storing image information.
Digital Image Column - Digital Image Column is the column or small pixel that is present at the y-axis.
Number of Pixels with Intensity Ri - Number of Pixels with Intensity Ri is the number of pixels that have intensity Ri.

STEP 1: Convert Input(s) to Base Unit

Number of Intensity Levels: 4 --> No Conversion Required
Digital Image Row: 9 --> No Conversion Required
Digital Image Column: 0.061 --> No Conversion Required
Number of Pixels with Intensity Ri: 2 --> No Conversion Required

STEP 2: Evaluate Formula

Substituting Input Values in Formula

s_k = ((L-1)/(M*N)*sum(x,0,L-1,n_j)) --> ((4-1)/(9*0.061)*sum(x,0,4-1,2))

Evaluating ... ...

s_k = 43.7158469945355

STEP 3: Convert Result to Output's Unit

43.7158469945355 --> No Conversion Required

FINAL ANSWER

43.7158469945355 ≈ 43.71585 <-- Discrete Form of Transformation

(Calculation completed in 00.004 seconds)

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Created by Zaheer Sheik

Seshadri Rao Gudlavalleru Engineering College (SRGEC), Gudlavalleru

Zaheer Sheik has created this Calculator and 25+ more calculators!

Verified by Dipanjona Mallick

Heritage Insitute of technology (HITK), Kolkata

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< 5 Intensity Transformation Calculators

Nth Moment of Discrete Random Variable

Go Nth Moment of Discrete Random Variable = sum(x,0,Number of Intensity Levels-1,Probability of Intensity Ri*(Pixel Intensity Level-Mean of Intensity Level)^Order of Moment)

Bits Required to Store Digitized Image

Go Bits in Digitized Image = Digital Image Row*Digital Image Column*Number of Bits

Bits Required to Store Square Image

Go Bits in Digitized Square Image = (Digital Image Column)^2*Number of Bits

Wavelength of Light

Go Wavelength of Light = [c]/Frequency of Light

Number of Intensity Levels

Go Number of Intensity Levels = 2^Number of Bits

Histogram Linearization Formula

What is Histogram Linearization?

Histogram linearization involves transforming the distribution of pixel values in an image's histogram into a more uniform or evenly spread out distribution. This process improves image contrast and brightness by redistributing pixel values. Techniques like histogram equalization or stretching are commonly used for histogram linearization, enhancing the overall appearance of the image.

How to Calculate Histogram Linearization?

Histogram Linearization calculator uses Discrete Form of Transformation = ((Number of Intensity Levels-1)/(Digital Image Row*Digital Image Column)*sum(x,0,Number of Intensity Levels-1,Number of Pixels with Intensity Ri)) to calculate the Discrete Form of Transformation, The Histogram Linearization formula is a process of transforming a histogram, which represents the distribution of pixel values in an image, into a linear distribution. Discrete Form of Transformation is denoted by s_k symbol.

How to calculate Histogram Linearization using this online calculator? To use this online calculator for Histogram Linearization, enter Number of Intensity Levels (L), Digital Image Row (M), Digital Image Column (N) & Number of Pixels with Intensity Ri (n_j) and hit the calculate button. Here is how the Histogram Linearization calculation can be explained with given input values -> 43.71585 = ((4-1)/(9*0.061)*sum(x,0,4-1,2)).

FAQ

What is Histogram Linearization?

The Histogram Linearization formula is a process of transforming a histogram, which represents the distribution of pixel values in an image, into a linear distribution and is represented as s_k = ((L-1)/(M*N)*sum(x,0,L-1,n_j)) or Discrete Form of Transformation = ((Number of Intensity Levels-1)/(Digital Image Row*Digital Image Column)*sum(x,0,Number of Intensity Levels-1,Number of Pixels with Intensity Ri)). Number of Intensity Levels is the total number of distinct intensity values an image can represent, determined by its bit depth, Digital Image Row is the row or small pixel that is present at the x-axis storing image information, Digital Image Column is the column or small pixel that is present at the y-axis & Number of Pixels with Intensity Ri is the number of pixels that have intensity Ri.

How to calculate Histogram Linearization?

The Histogram Linearization formula is a process of transforming a histogram, which represents the distribution of pixel values in an image, into a linear distribution is calculated using Discrete Form of Transformation = ((Number of Intensity Levels-1)/(Digital Image Row*Digital Image Column)*sum(x,0,Number of Intensity Levels-1,Number of Pixels with Intensity Ri)). To calculate Histogram Linearization, you need Number of Intensity Levels (L), Digital Image Row (M), Digital Image Column (N) & Number of Pixels with Intensity Ri (n_j). With our tool, you need to enter the respective value for Number of Intensity Levels, Digital Image Row, Digital Image Column & Number of Pixels with Intensity Ri and hit the calculate button. You can also select the units (if any) for Input(s) and the Output as well.

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