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## DIG IMAGE PROC & ANALY

by: Brendan Kling

21

0

3

# DIG IMAGE PROC & ANALY GEOG 661

Marketplace > Texas A&M University > Geography > GEOG 661 > DIG IMAGE PROC ANALY
Brendan Kling
Texas A&M
GPA 3.78

Staff

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COURSE
PROF.
Staff
TYPE
Class Notes
PAGES
3
WORDS
KARMA
25 ?

## Popular in Geography

This 3 page Class Notes was uploaded by Brendan Kling on Wednesday October 21, 2015. The Class Notes belongs to GEOG 661 at Texas A&M University taught by Staff in Fall. Since its upload, it has received 21 views. For similar materials see /class/225772/geog-661-texas-a-m-university in Geography at Texas A&M University.

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Date Created: 10/21/15
Quantization Introduction Quantization is the digitization of the amplitude of the function More precisely it is the process by which each amplitude in a continuous image is assigned a new value from a nite set of gray values GV or as they are more commonly referred to digital numbers The term DN is used because the values used are commonly positive integers The interval between adjacent values is the quantization interval AV Most commonly the interval is constant through the range of function values though for speci c cases unequal intervals may be preferred 15 ma writang is min 5 v0 I n LC ILl me Lumx quot 2 s Radiance L The gure above illustrates the relationship between the voltage produced by a detector in response to radiation incident upon it v0 is called the dark current v1 and v2 indicate the range of voltages over which v is linearly proportional to the radiance vmm and va are the range of voltages which are to be digitized and Av is the quantization interval 7 it needs to be greater or equal to the noise Any voltage in the red area will be assigned the same digiml number The dynamic range of the function is the difference between the minimum and maximum signals where the lower limit is called the dark current and the upper limit is called saturation The ideal quantization interval is the size ofor slightly greater than the system noise since this choice will minimize system noise without any substantial reduction of the signal However the actual quantization interval is constrained by the total number ofDN values possible This in turn is Vm Vl limited by the number ofbits ofinformation designated for each pixel The common 8 bit byte will allow 256 DN values but newer system are 12 4096 DNs or 16 bit 65536 DNs The actual voltage interval Av is related to the number ofDN values as follows where b is the number ofbits in the digitized image The following mble conmins some common bit values and there corresponding number ofDN values 1 127 32768 Some Examples of Quantization

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