sampling and Quantization in digitization

Digitization

2. •The sensors produce an image in the form of an
analogsignal, which is then digitized to produce a
digital image.
•A digital image is a two-dimensional f(x,y)
functionwhereandindicate the position in an
image.
•Thefunction holds a discrete value called
theintensity value.
•Let’s see an example of the visual representation of
spatial coordinates and amplitude of a digital image:
•The digital image contains a collection of elements
called pixel or picture elements,each having its
intensity value. In order to enhance an image and use
it for some applications, we apply various operations
that are part of the image processing method.
•Sampling and quantization operations are part of the
image processing method that converts continuous
voltage signals obtained from sensors into digital
images.

4. •Digital images are basically of three types:
monochrome or binary images, grayscaleimages, and
colorimages.
•The pixel value of a binary image at a specific
location(x,y)usually holds the value 0 for black or 1 for
white.
•Grayscaleimages have intensity values ranging from 0
to 255, where 0 is black, gradually fading to 255, which
is white.
•Additionally, colorimages like RGB images contain three
channels red, green, and blue channels. Each channel in
an RGB image has intensity values ranging from 0-255.

5. Let’s see how each image looks with the help
of 4×4 samples from binary, grayscale, and
RGB image:
Sampling and quantization result in a matrix of rows
and columns consisting of real numbers.
Further, let’s say a photo is 250 x 350. Here, the width is
250, and the image height is 350.
This implies that the digital image has 250 columns and
350 rows, respectively.

12. •Multispectral images typically contain
information outside the normal human
perceptual range. This may include IR, UV, X-ray,
acoustic or radar data.
•These are not image in the usual sense because
the information represented is not directly visible
by the human system.
•However the information is often represented in
visual form by mapping the different spectral
bands to RGB components.

17. Digitization

18. Image Sampling

19. Sampling & Quantization

25. Sampling & Quantization

28. Digitization

30. Sampling versus Quantization

32. Representation of Digital Image

39. •The sampling rate determines the spatial
resolution of the digitized image, while the
quantization level determines the number of grey
levels in the digitized image.
•A magnitude of the sampled image is expressed
as a digital value in image processing.
•The transition between continuous values of the
image function and its digital equivalent is called
quantization.

40. Result of Quantization

41. •Spatial Resolution in Digital Images
•Spatial resolution is a term that refers to the
number of pixels utilized in construction of a
digital image. Images having higher spatial
resolution are composed with a greater
number of pixels than those of lower spatial
resolution.

42. •Spatial resolution and Resolution intensity are terms used
inimage resolution or clarity of image.
•In simple terms, images are referred to as blurred or sharp,
depending on the intensity of resolution.
•Intensity of resolutionmeans the number of pixels per
square inch, which determines the clarity or sharpness of
an image.
•Spatial resolutionrefers to the number of pixels used in
making an image.
•Images with a higher number of pixels per square inch are
sharp and hence said to have a higher Spatial resolution.
Such images are very clear.