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Fundamentals Rawesak Tanawongsuwan [email protected]

Fundamentals Rawesak Tanawongsuwan [email protected]

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Page 1: Fundamentals Rawesak Tanawongsuwan ccrtw@mahidol.ac.th

Fundamentals

Rawesak [email protected]

Page 2: Fundamentals Rawesak Tanawongsuwan ccrtw@mahidol.ac.th

Digital Data

• Bits are units of data that can only have one of two values.

• A byte is eight bits.• Groups of bits can be interpreted as numbers

to base 2, but can also be treated as characters, colours, etc.

Page 3: Fundamentals Rawesak Tanawongsuwan ccrtw@mahidol.ac.th

Bytes to remember

• 1 byte = 8 bits• 2 bytes = 16 bits• 3 bytes = 24 bits• 4 bytes = 32 bits• .• .• .

Page 4: Fundamentals Rawesak Tanawongsuwan ccrtw@mahidol.ac.th

Analogue and Digital Representation

Page 5: Fundamentals Rawesak Tanawongsuwan ccrtw@mahidol.ac.th

Digitization

• Converting a signal from analogue to digital form– Analogue signal can vary continuously, digital is

restricted to discrete values• Two-stage process– Sampling – measure the value at discrete intervals– Quantization – restrict the value to a fixed set of

quantization levels

Page 6: Fundamentals Rawesak Tanawongsuwan ccrtw@mahidol.ac.th

Sampling and Quantization

Page 7: Fundamentals Rawesak Tanawongsuwan ccrtw@mahidol.ac.th

Sampling and Quantization

• The sampling rate is the number of samples in a fixed amount of time or space.

• The quantization levels are the set of values to which a signal is quantized.

Page 8: Fundamentals Rawesak Tanawongsuwan ccrtw@mahidol.ac.th

Analogue vs Digital

Page 9: Fundamentals Rawesak Tanawongsuwan ccrtw@mahidol.ac.th

Benefits of digital signals

• High fidelity• Noise tolerance

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Frequency Domain

• Any periodic waveform can be decomposed into a collection of frequency components– Each one is a pure sine wave

• The collection of frequencies and their amplitudes represent the waveform in the frequency domain– Compute the frequency domain representation

(frequency spectrum) using the Fourier Transform

– Higher frequency components are associated with abrupt transitions

Page 11: Fundamentals Rawesak Tanawongsuwan ccrtw@mahidol.ac.th

Spatial and temporal signals

• Spatial and temporal signals are made up of pure sine wave components at different frequencies.

• The Fourier Transform operation can be used to compute a signal’s representation in the frequency domain.

• Higher-frequency components are associated with abrupt transitions.

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Page 13: Fundamentals Rawesak Tanawongsuwan ccrtw@mahidol.ac.th

Sampling Theorem

• If the highest frequency component of a signal is at fh the signal can be properly reconstructed if it has been sampled at a frequency > 2fh– Nyquist rate

• Undersamping leads to aliasing– Sound distortion, image 'jaggies' or Moiré

patterns, jerky or retrograde motion

Page 14: Fundamentals Rawesak Tanawongsuwan ccrtw@mahidol.ac.th

Aliasing

Anti-aliased

Aliased

Page 15: Fundamentals Rawesak Tanawongsuwan ccrtw@mahidol.ac.th

Aliasing

Page 16: Fundamentals Rawesak Tanawongsuwan ccrtw@mahidol.ac.th

Moiré Patterns

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Too Few Quantization Levels

• Reducing memory requirements by using fewer bits for each value means fewer quantization levels are available

• Cannot distinguish between values that fall between levels

• Images: banding and posterization• Sound: coarse hiss, loss of quiet passages,

general fuzziness (quantization noise)

Page 18: Fundamentals Rawesak Tanawongsuwan ccrtw@mahidol.ac.th

Image banding effects

Page 19: Fundamentals Rawesak Tanawongsuwan ccrtw@mahidol.ac.th

Posterization

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Digital Representation of Media

• There are established ways of representing images, video, animation, sound and text in bits.

• Media data may be represented as a textual description in a suitable language, or as binary data with a specific structural form.

Page 21: Fundamentals Rawesak Tanawongsuwan ccrtw@mahidol.ac.th

Image

• Images are displayed as arrays of pixels and represented using an internal model. Generating the pixels from the model is called rendering.

Page 22: Fundamentals Rawesak Tanawongsuwan ccrtw@mahidol.ac.th

Bitmaps vs Vector Graphics

• Images may be modelled as bitmaps or vector graphics.

• A bitmap is an array of logical pixels (stored colour values) that can be mapped directly to the physical pixels on the display.

• In vector graphics, the image is stored as a mathematical description of a collection of individual lines, curves and shapes making up the image, which requires computation to render it.

Page 23: Fundamentals Rawesak Tanawongsuwan ccrtw@mahidol.ac.th
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Page 25: Fundamentals Rawesak Tanawongsuwan ccrtw@mahidol.ac.th

Good Things for Vector Graphics

• Often smaller than bitmaps• Resolution-independent• Scalable without loss of quality – only suitable for certain sorts of synthetic image,

not photographs

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Combining Vectors & Bitmaps

• Rasterize vectors– Lose all their vector properties

• Trace bitmaps– Difficult and can only produce an approximation

(parameterized)

Page 30: Fundamentals Rawesak Tanawongsuwan ccrtw@mahidol.ac.th

Layers

• Organizational device used in both sorts of graphics, especially useful in bitmaps– Permits separation and manipulation of different

parts of a bitmapped image• Digital version of clear sheets of acetate,

stacked on top of each other– Areas without coloured pixels/graphic objects are

transparent so lower layers show through• Compositing – combine layers using different

blending modes (digital collage)

Page 31: Fundamentals Rawesak Tanawongsuwan ccrtw@mahidol.ac.th

Creatively Blending Layers

http://www.carlvolk.com/photoshop15.htm

Page 32: Fundamentals Rawesak Tanawongsuwan ccrtw@mahidol.ac.th

Creatively Blending Layers

http://www.carlvolk.com/photoshop15.htm

Page 33: Fundamentals Rawesak Tanawongsuwan ccrtw@mahidol.ac.th

Graphics/Image Data Types

Page 34: Fundamentals Rawesak Tanawongsuwan ccrtw@mahidol.ac.th

RGB Components

Page 35: Fundamentals Rawesak Tanawongsuwan ccrtw@mahidol.ac.th

Moving pictures, Videos, Animation

• Moving pictures can be created as live-action or animation.

• Live-action must be stored as video.• Animation may be represented in other more

flexible or efficient ways.• Video frames require a lot of storage so video

is invariably compressed for delivery.

Page 36: Fundamentals Rawesak Tanawongsuwan ccrtw@mahidol.ac.th
Page 37: Fundamentals Rawesak Tanawongsuwan ccrtw@mahidol.ac.th

Sound

• Sound can be represented as a sequence of samples after digitization.

• CD audio is sampled at 44.1 kHz, higher sampling rates are sometimes used.

• Audio delivered over the Internet is compressed, often using the MP3 codec.

Page 38: Fundamentals Rawesak Tanawongsuwan ccrtw@mahidol.ac.th

Text

• A character set is a mapping from characters to character codes.

• Unicode is a character set capable of representing text in all known languages.

• A font is a set of character shapes, called glyphs.

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Page 40: Fundamentals Rawesak Tanawongsuwan ccrtw@mahidol.ac.th

Layout and Typography

• Many aspects of layout must be controlled when text is displayed.

Page 41: Fundamentals Rawesak Tanawongsuwan ccrtw@mahidol.ac.th

Interactivity

• Interactivity is produced by executing a program in response to user input.

• In multimedia, programs are often written in a scripting language, such as JavaScript or ActionScript.

Page 42: Fundamentals Rawesak Tanawongsuwan ccrtw@mahidol.ac.th

Compression

• Compression must often be applied to media data.

• Compression may be lossless or lossy.– Lossless – image can be reconstructed exactly

from compressed version– Lossy – some information discarded, image can

only be reconstructed approximately

Page 43: Fundamentals Rawesak Tanawongsuwan ccrtw@mahidol.ac.th
Page 44: Fundamentals Rawesak Tanawongsuwan ccrtw@mahidol.ac.th

Compression

• Different compression algorithms are applicable to different types of media data. Their effectiveness depends on the characteristics of the data itself.