MULTIMEDIA
1. Image Types and Representations
Bitmap Images
• Made up of individual pixels arranged in rows and columns.
• Each pixel is a single square of one color (the smallest addressable unit in an image).
• When you zoom in or enlarge a bitmap image, it becomes pixelated.
• File size is larger due to storing color data for every pixel.
• Bitmap image compression is effective because redundant pixel data can be reduced.
Vector Graphics
• Made up of drawing objects (e.g. circles, lines, polygons).
• Stores a set of instructions or mathematical formulas to draw shapes.
• Scalable without losing quality — does not pixelate.
• Smaller file size because it stores commands, not pixels.
• Does not compress well (little redundant data).
• Suitable for geometric and flat-color images (e.g., logos).
2. Image Properties
Image Resolution
• Measured in pixels per inch (PPI).
• Higher resolution: More detail, more pixels per inch, sharper image.
• Lower resolution: Less detail, fewer pixels per inch, more pixelated.
Screen Resolution
• Number of pixels visible horizontally and vertically on a display screen.
Color Depth / Bit Depth
• Number of bits used per pixel to represent color.
• Higher bit depth = more color combinations (e.g., 8-bit = 256 colors).
• Formula: 2^n where n is the number of bits.
• Higher color depth = more accurate and realistic images, but larger file size.
3. Bitmap Image Metadata
Metadata
• Data about data, e.g. filename, file format, color depth.
File Header
• Contains data such as:
o Image size
o Number of pixels
o Compression type
o Color depth
o File location
4. File Size Calculation for Images
Formula:
File Size (bits) = Width (pixels) × Height (pixels) × Color Depth (bits per pixel)
Example:
An image of 4x4 pixels with 2 bits per pixel:
4 × 4 × 2 = 32 bits
5. Vector Graphic Key Terms
• Drawing List: A list of all the objects in the image and the instructions to draw them.
• Drawing Objects: The shapes used to build complex objects.
• Properties: Attributes of each object, like color, size, and border thickness.
6. Comparison: Bitmap vs Vector Graphics
Feature Bitmap Vector
Composition Pixels Instructions for shapes
Scalability Becomes pixelated when resized Scales without quality loss
File Size Larger Smaller
Compression Effective Not effective
Best Used For Photos, detailed images Logos, diagrams, flat-color shapes
7. Binary vs Decimal Prefixes
Prefix Binary (Base 2) Decimal (Base 10)
Kilobyte 1 KiB = 1024 bytes 1 KB = 1000 bytes
Megabyte 1 MiB = 1024 KiB 1 MB = 1000 KB
Gigabyte 1 GiB = 1024 MiB 1 GB = 1000 MB
Terabyte 1 TiB = 1024 GiB 1 TB = 1000 GB
8. Graphic Editing Software Features
• Resize (change image dimensions)
• Crop (remove unwanted parts)
• Blur (reduce focus/detail)
• Red-Eye Reduction (fix red eye effect)
• Audio Editing:
o Edit start/stop times
o Delete clips
o Fade in/out
o Mix soundtracks
o Apply filters
o Convert audio formats
9. Sound Representation
Analogue vs Digital
• Analogue: Continuous wave (real-world sounds).
• Digital: Discrete values (stored as binary).
Sampling
• Sampling: Measuring amplitude of sound at regular intervals.
• Sampling Rate: Number of samples taken per second (Hz).
• Sampling Resolution: Number of bits per sample.
Quantization Error
• The difference between the original analogue value and the digital approximation.
10. Impacts of Sampling Rate & Resolution
Increasing Sampling Rate
• More accurate representation of sound.
• Smaller gaps between samples.
• Reduced quantization error.
• Larger file size.
Increasing Sampling Resolution
• More bits = more amplitude values.
• Reduces quantization error.
• Increases file size and storage requirements.
11. File Size Calculation for Sound
Formula:
File Size (bits) = Sampling Rate × Duration (seconds) × Sampling Resolution
12. Example Questions (Exam Style)
Q: Describe how increasing sampling rate affects a sound recording:
• Sound is recorded more frequently.
• Digital waveform is closer to analogue.
• Smaller quantization error.
• Larger file size.
Q: Describe the contents of a vector drawing list:
• List of drawing objects.
• Instructions for how to draw them.
• Object properties like fill color and border thickness.
Q: Explain the difference between bitmap and vector graphics:
• Bitmap: Pixel-based, scalable with pixelation.
• Vector: Instruction-based, scalable without quality loss.
Compression: Reduction of File Size
Why Do We Need to Compress a File?
• Data files are often large
• Non-compressed files take longer to transmit
• Compressed files download faster
• Reduces need for high bandwidth (rate of data transfer)
Types of Compression
• Lossless Compression:
o No data is lost
o Compressed file can be restored to original
• Lossy Compression:
o Some data is permanently removed
o Decompressed file is not the same as the original
Applications of Lossy and Lossless Compression
• Lossless:
o Used when accuracy is important (e.g., software source code)
o Example: Abdullah compressing a program file
• Lossy:
o Used when accuracy is less important, smaller file size is prioritized
o Example: Compressing a photograph to be emailed
Bitmap Image Compression
• Lossless Method: Run-Length Encoding (RLE):
o Detects consecutive pixels of the same color
o Stores one color value and the count of repetitions
• Lossy Methods:
o JPEG: Removes unnoticeable parts of the image to human eyes
o Crop: Removes entire sections (lossy)
o Reduce Bit Depth: Fewer bits per pixel
o Reduce Color Count: Fewer colors stored
o Reduce Image Resolution: Fewer pixels per area
Vector Image Compression
• Run-Length Encoding (RLE):
o Replaces repeated characters in file with a count + value
o Example: "AAAABBB" becomes "4A3B"
Sound Compression
• Lossy Methods:
o Perceptual Music Shaping: Removes inaudible frequencies and quieter simultaneous sounds
o Reduce Sampling Resolution: Fewer bits per sample
o Reduce Sampling Rate: Fewer samples per second
• Lossless Methods:
o Reduce amplitude range
o Run-Length Encoding: Records repeated values as one value and count
o Delta Encoding: Store change from previous sample instead of full amplitude
Text File Compression
• Lossless Compression:
o Run-Length Encoding: Replace repeated characters with count and character
• Why Not Use Lossy Compression for Text?
o Loss of any data corrupts the file
o File may become unreadable or unopenable
Benefits of Compressing Photographs for Customers
• Faster download
• Less bandwidth usage
• Less storage space required
• More space available for other files
