Mean Value of Pixels in Neighborhood Solution

STEP 0: Pre-Calculation Summary
Formula Used
Subimage Pixel Mean Intensity Level = sum(x,0,Number of Intensity Levels-1,Pixel Intensity Level*Probability of Occurrence of Rith in Subimage)
mSxy = sum(x,0,L-1,ri*pSxy_ri)
This formula uses 1 Functions, 4 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
Subimage Pixel Mean Intensity Level - Subimage Pixel Mean Intensity Level represents the mean intensity level of pixels in the subimage S_xy.
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.
Pixel Intensity Level - (Measured in Watt per Square Meter) - Pixel Intensity Level refer to the range of possible intensity values that can be assigned to pixels in an image. This concept is particularly relevant in grayscale images.
Probability of Occurrence of Rith in Subimage - Probability of Occurrence of Rith in Subimage represents the probability of occurrence of the intensity level r_i within the subimage S_xy.
STEP 1: Convert Input(s) to Base Unit
Number of Intensity Levels: 4 --> No Conversion Required
Pixel Intensity Level: 15 Watt per Square Meter --> 15 Watt per Square Meter No Conversion Required
Probability of Occurrence of Rith in Subimage: 0.25 --> No Conversion Required
STEP 2: Evaluate Formula
Substituting Input Values in Formula
mSxy = sum(x,0,L-1,ri*pSxy_ri) --> sum(x,0,4-1,15*0.25)
Evaluating ... ...
mSxy = 15
STEP 3: Convert Result to Output's Unit
15 --> No Conversion Required
FINAL ANSWER
15 <-- Subimage Pixel Mean Intensity Level
(Calculation completed in 00.004 seconds)

Credits

Creator Image
Created by Zaheer Sheik
Seshadri Rao Gudlavalleru Engineering College (SRGEC), Gudlavalleru
Zaheer Sheik has created this Calculator and 25+ more calculators!
Verifier Image
Verified by Dipanjona Mallick
Heritage Insitute of technology (HITK), Kolkata
Dipanjona Mallick has verified this Calculator and 50+ more calculators!

Intensity Transformation Calculators

Bits Required to Store Digitized Image
​ LaTeX ​ Go Bits in Digitized Image = Digital Image Row*Digital Image Column*Number of Bits
Bits Required to Store Square Image
​ LaTeX ​ Go Bits in Digitized Square Image = (Digital Image Column)^2*Number of Bits
Wavelength of Light
​ LaTeX ​ Go Wavelength of Light = [c]/Frequency of Light
Number of Intensity Levels
​ LaTeX ​ Go Number of Intensity Levels = 2^Number of Bits

Mean Value of Pixels in Neighborhood Formula

​LaTeX ​Go
Subimage Pixel Mean Intensity Level = sum(x,0,Number of Intensity Levels-1,Pixel Intensity Level*Probability of Occurrence of Rith in Subimage)
mSxy = sum(x,0,L-1,ri*pSxy_ri)

What is the Mean Value of Pixels in Neighborhood?

The global mean and variance are computed over an entire image and are useful for gross adjustments in overall intensity and contrast. A more powerful use of these parameters is in local enhancement, where the local mean and variance are used as the basis for making changes that depend on image characteristics in a neighborhood about each pixel in an image.

How to Calculate Mean Value of Pixels in Neighborhood?

Mean Value of Pixels in Neighborhood calculator uses Subimage Pixel Mean Intensity Level = sum(x,0,Number of Intensity Levels-1,Pixel Intensity Level*Probability of Occurrence of Rith in Subimage) to calculate the Subimage Pixel Mean Intensity Level, The Mean Value of Pixels in Neighborhood formula is used to find global mean which is computed over an entire image and are useful for gross adjustments in overall intensity and contrast. Subimage Pixel Mean Intensity Level is denoted by mSxy symbol.

How to calculate Mean Value of Pixels in Neighborhood using this online calculator? To use this online calculator for Mean Value of Pixels in Neighborhood, enter Number of Intensity Levels (L), Pixel Intensity Level (ri) & Probability of Occurrence of Rith in Subimage (pSxy_ri) and hit the calculate button. Here is how the Mean Value of Pixels in Neighborhood calculation can be explained with given input values -> 15 = sum(x,0,4-1,15*0.25).

FAQ

What is Mean Value of Pixels in Neighborhood?
The Mean Value of Pixels in Neighborhood formula is used to find global mean which is computed over an entire image and are useful for gross adjustments in overall intensity and contrast and is represented as mSxy = sum(x,0,L-1,ri*pSxy_ri) or Subimage Pixel Mean Intensity Level = sum(x,0,Number of Intensity Levels-1,Pixel Intensity Level*Probability of Occurrence of Rith in Subimage). Number of Intensity Levels is the total number of distinct intensity values an image can represent, determined by its bit depth, Pixel Intensity Level refer to the range of possible intensity values that can be assigned to pixels in an image. This concept is particularly relevant in grayscale images & Probability of Occurrence of Rith in Subimage represents the probability of occurrence of the intensity level r_i within the subimage S_xy.
How to calculate Mean Value of Pixels in Neighborhood?
The Mean Value of Pixels in Neighborhood formula is used to find global mean which is computed over an entire image and are useful for gross adjustments in overall intensity and contrast is calculated using Subimage Pixel Mean Intensity Level = sum(x,0,Number of Intensity Levels-1,Pixel Intensity Level*Probability of Occurrence of Rith in Subimage). To calculate Mean Value of Pixels in Neighborhood, you need Number of Intensity Levels (L), Pixel Intensity Level (ri) & Probability of Occurrence of Rith in Subimage (pSxy_ri). With our tool, you need to enter the respective value for Number of Intensity Levels, Pixel Intensity Level & Probability of Occurrence of Rith in Subimage 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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