1. JASHORE UNIVERSITY OF SCIENCE AND TECHNOLOGY
DEPARTMENT OF BIOMEDICAL ENGINEERING
Presentation topics: Image Quantization
Kazim
2. What is image quantization?
Quantization is the process of mapping a large set of input values to output values in a countable smaller set.
Or
Quantization is a lossy compression technique achieved by compressing a range of values to a single
quantum (discrete) value
Quantizer
Input values Output values
3. Concept of quantization:
Quantization is opposite to sampling. It is done on y-axis. When we quantize an image, we actually divide
a signal into quanta(partitions).
The co-ordinate values are on the x-axis of the signal, and on the y-axis, we have amplitudes. So digitizing
the amplitudes is known as Quantization.
You can see in this image, that the signal has been quantified
into three different levels. That means that when we sample
an image, we actually gather a lot of values, and in quantization,
we set levels to these values
4. In the image showed in sampling explanation, although the samples has been taken, but they
were still spanning vertically to a continuous range of gray level values. In the image shown
below, these vertically ranging values have been quantized into 5 different levels or partitions.
Ranging from 0 black to 4 white. This level could vary according to the type of image we want.
5. Step in quantization:
Number of quantization level: 2𝑏
Where, b-bits per pixel are used.
Total range is divide into q equal intervals of step size S
S=
𝑉𝐻−𝑉𝐿
𝑞
=
𝑉𝐻−𝑉𝐿
2𝑛 where, 𝑉𝐻=Max. value
𝑉𝐿= Min. value
Draw midlines representing quantization levels.
Assign binary codes ( pre-defined) to each quantization level.
Calculate quantization error.
6. Quantization Error:
The difference between sampled signal to quantized signal is called quantization error. It can reduce
by increasing quantization level or number of bit.
e[n]= 𝑥𝑞 𝑛 − 𝑥[𝑛]
7. Advantages of quantization:
The quantized signal, which is an approximation of the original signal, can be more
efficiently separated from ADDITIVE NOISE.
Transmission bandwidth can be controlled by using an appropriate number of
quantization levels (and hence the bit to represent them).
It reduces the number of bits used to represent a signal.
low cost, increased reliability, and effective transmission.
