✖Nominal Dynamic Range is the range of signal amplitudes within which a system is expected to operate optimally, providing faithful reproduction or transmission of information.ⓘ Nominal Dynamic Range [R_b]			+10% -10%
✖Bits Allotted Exponent Number represent the number of binary digits reserved for encoding the exponent component of a floating-point number, determining its range and precision.ⓘ Bits Allotted Exponent Number [ε_b]			+10% -10%
✖Bits Allotted to Mantissa Number represent the number of binary digits reserved for encoding the fractional part of a floating-point number, determining its precision and range.ⓘ Bits Allotted to Mantissa Number [μ_b]			+10% -10%

✖Quantization Step Size is the difference between two adjacent quantization levels. It determines the spacing or granularity of the quantization.ⓘ Quantization Step Size in Image Processing [Δ_b]

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Quantization Step Size in Image Processing

Formula

`"Δ"_{"b"} = (2^("R"_{"b"}-"ε"_{"b"}))*(1+"μ"_{"b"}/2^11)`

Example

`"443.1024kW/m²"=(2^("21dB"-"2.245"))*(1+"3.24"/2^11)`

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Quantization Step Size in Image Processing Solution

STEP 0: Pre-Calculation Summary

Formula Used

Quantization Step Size = (2^(Nominal Dynamic Range-Bits Allotted Exponent Number))*(1+Bits Allotted to Mantissa Number/2^11)
Δ_b = (2^(R_b-ε_b))*(1+μ_b/2^11)
This formula uses 4 Variables

Variables Used

Quantization Step Size - (Measured in Watt per Square Meter) - Quantization Step Size is the difference between two adjacent quantization levels. It determines the spacing or granularity of the quantization.
Nominal Dynamic Range - (Measured in Decibel) - Nominal Dynamic Range is the range of signal amplitudes within which a system is expected to operate optimally, providing faithful reproduction or transmission of information.
Bits Allotted Exponent Number - Bits Allotted Exponent Number represent the number of binary digits reserved for encoding the exponent component of a floating-point number, determining its range and precision.
Bits Allotted to Mantissa Number - Bits Allotted to Mantissa Number represent the number of binary digits reserved for encoding the fractional part of a floating-point number, determining its precision and range.

STEP 1: Convert Input(s) to Base Unit

Nominal Dynamic Range: 21 Decibel --> 21 Decibel No Conversion Required
Bits Allotted Exponent Number: 2.245 --> No Conversion Required
Bits Allotted to Mantissa Number: 3.24 --> No Conversion Required

STEP 2: Evaluate Formula

Substituting Input Values in Formula

Δ_b = (2^(R_b-ε_b))*(1+μ_b/2^11) --> (2^(21-2.245))*(1+3.24/2^11)

Evaluating ... ...

Δ_b = 443102.390695357

STEP 3: Convert Result to Output's Unit

443102.390695357 Watt per Square Meter -->443.102390695357 Kilowatt per Square Meter (Check conversion here)

FINAL ANSWER

443.102390695357 ≈ 443.1024 Kilowatt per Square Meter <-- Quantization Step Size

(Calculation completed in 00.004 seconds)

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< 17 Basics of Image Processing Calculators

Standard Deviation by Linear Function of Camera Exposure Time

Go Standard Deviation = Model Function*(Radiant Intensity)*Model Behaviour Function*(1/Distance between Camera and the IRED^2)*(Model Coefficient 1*Camera Exposure Time+Model Coefficient 2)

Bilinear Interpolation

Go Bilinear Interpolation = Coefficient a*X Co-ordinate+Coefficient b*Y Co-ordinate+Coefficient c*X Co-ordinate*Y Co-ordinate+Coefficient d

Linear Combination of Expansion

Go Linear Combination of Expansion Functions = sum(x,0,Integer Index for Linear Expansion,Real Valued Expansion Coefficients*Real Valued Expansion Functions)

Cumulative Frequency for Each Brightness Value

Go Cumulative Frequency for Each Brightness = 1/Total Number of Pixels*sum(x,0,Maximum Brightness Value,Frequency of Occurrence of Each Brightness Value)

Band Loads Associated with Principle Components

Go K Band Loads with P Principle Components = Eigen Band k Component P*sqrt(Pth Eigenvalue)/sqrt(Band Variance Matrix)

Run-Length Entropy of Image

Go Run Length Entropy Image = (Entropy Black Run Length+Entropy of White Run Length)/(Average Black Run Length+Average White Run Length)

Wavelet Coefficient

Go Detail Wavelet Coefficient = int(Scaling Function Expansion*Wavelet Expansion Function*x,x,0,Integer Index for Linear Expansion)

Quantization Step Size in Image Processing

Go Quantization Step Size = (2^(Nominal Dynamic Range-Bits Allotted Exponent Number))*(1+Bits Allotted to Mantissa Number/2^11)

Digital Image Row

Go Digital Image Row = sqrt(Number of Bits/Digital Image Column)

Digital to Analog Converter

Go Digital to Analog Converter Resolution = Reference Voltage Image/(2^Number of Bits-1)

Rejection of Image Frequency

Go Customer Selling Price = (1+Quality Factor Image^2*Rejection Constant Image^2)^0.5

Probability of Intensity Level Occurring in given Image

Go Probability of Intensity = Intensity Occurs in Image/Total Number of Pixels

Digital Image Column

Go Digital Image Column = Number of Bits/(Digital Image Row^2)

Number of Bits

Go Number of Bits = (Digital Image Row^2)*Digital Image Column

Image File Size

Go Image File Size = Image Resolution*Bit Depth/8000

Energy of Various Components

Go Energy of Component = [hP]*Frequency

Number of Grey Level

Go Grey Level Image = 2^Digital Image Column

Quantization Step Size in Image Processing Formula

Quantization Step Size = (2^(Nominal Dynamic Range-Bits Allotted Exponent Number))*(1+Bits Allotted to Mantissa Number/2^11)
Δ_b = (2^(R_b-ε_b))*(1+μ_b/2^11)

How does the quantization step size affect image quality?

The quantization step size is inversely proportional to image quality. A smaller step size results in finer quantization levels and higher image fidelity, while a larger step size leads to a coarser representation with lower image quality.

How to Calculate Quantization Step Size in Image Processing?

Quantization Step Size in Image Processing calculator uses Quantization Step Size = (2^(Nominal Dynamic Range-Bits Allotted Exponent Number))*(1+Bits Allotted to Mantissa Number/2^11) to calculate the Quantization Step Size, The Quantization Step Size in Image Processing formula is defined as the process of reducing the number of distinct intensity levels in an image. It also determines the size of the intervals between the quantized levels. Quantization Step Size is denoted by Δ_b symbol.

How to calculate Quantization Step Size in Image Processing using this online calculator? To use this online calculator for Quantization Step Size in Image Processing, enter Nominal Dynamic Range (R_b), Bits Allotted Exponent Number (ε_b) & Bits Allotted to Mantissa Number (μ_b) and hit the calculate button. Here is how the Quantization Step Size in Image Processing calculation can be explained with given input values -> 443102.4 = (2^(21-2.245))*(1+3.24/2^11).

FAQ

What is Quantization Step Size in Image Processing?

The Quantization Step Size in Image Processing formula is defined as the process of reducing the number of distinct intensity levels in an image. It also determines the size of the intervals between the quantized levels and is represented as Δ_b = (2^(R_b-ε_b))*(1+μ_b/2^11) or Quantization Step Size = (2^(Nominal Dynamic Range-Bits Allotted Exponent Number))*(1+Bits Allotted to Mantissa Number/2^11). Nominal Dynamic Range is the range of signal amplitudes within which a system is expected to operate optimally, providing faithful reproduction or transmission of information, Bits Allotted Exponent Number represent the number of binary digits reserved for encoding the exponent component of a floating-point number, determining its range and precision & Bits Allotted to Mantissa Number represent the number of binary digits reserved for encoding the fractional part of a floating-point number, determining its precision and range.

How to calculate Quantization Step Size in Image Processing?

The Quantization Step Size in Image Processing formula is defined as the process of reducing the number of distinct intensity levels in an image. It also determines the size of the intervals between the quantized levels is calculated using Quantization Step Size = (2^(Nominal Dynamic Range-Bits Allotted Exponent Number))*(1+Bits Allotted to Mantissa Number/2^11). To calculate Quantization Step Size in Image Processing, you need Nominal Dynamic Range (R_b), Bits Allotted Exponent Number (ε_b) & Bits Allotted to Mantissa Number (μ_b). With our tool, you need to enter the respective value for Nominal Dynamic Range, Bits Allotted Exponent Number & Bits Allotted to Mantissa Number 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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