Decision Making

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INTRODUCTION TO IMAGE PROCESSING

Lecture 8 Syed Kashif Iqbal

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DIGITAL IMAGE FUNDAMENTALS

Chapter 2 Section 2.3 Section 2.4 Digital Image processing (3rd edition) by Gonzales R.C and Woods R.E

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Objectives of the lecture

• Image Sampling and Quantization

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Image Sampling and Quantization

• Let us consider a continuous image having infinite

coordinate levels (x,y) and infinite Amplitude f(x,y). • To convert it to digital form, we have to sample/digitize (limit the representation of data) the function in both coordinates and in amplitude. • An image may be continuous with respect to the x- and ycoordinates, and also in amplitude.

• Digitizing the coordinate values is called sampling. • Digitizing the amplitude values is called quantization.

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Sampling

• Digitizing the coordinate values is called sampling.

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Sampling

• Digitizing the coordinate values is called sampling.

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Sampling

• From the continuous image show the intensity values under the line AB • Digitize the coordinate values also called sampling. • To sample the continuous function, we take equally spaced samples along

line AB • The spatial location of each sample is indicated by a vertical tick mark in the bottom part of the figure. The samples are shown as small white squares superimposed on the function.

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Quantization

• Digitizing the amplitude values is called quantization.

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Sampling and Quantization

• Quantize the Image in Spatial domain

• Quantize the amplitude values of the image.

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Representing Digital Images

• Let a function f(x,y) represent a continuous image

• We convert this function into a digital image by sampling

and quantization, containing M rows and N columns. • x = 0, 1, 2, ....., M - 1 y = 0, 1, 2, ......, N - 1

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Representing Digital Images

• Each element of this matrix is called an image element,

picture element, pixel, or pel. • This is a conventional representation based on the...