1.2.3 | IMAGE REPRESENTATION
Topics from the Cambridge IGCSE (9-1) Computer Science 0984 syllabus 2023 - 2025.
OBJECTIVES
1.2.3 Understand how and why a computer represents an image, including the effects of the resolution and colour depth
1.2.3 Understand how and why a computer represents an image, including the effects of the resolution and colour depth
WHAT IS IMAGE REPRESENTATION?
Just as numbers and letters are represented with Binary, so are images. To a computer an image is nothing more than a series of ones and zeros which allow the display of pixels in various colours.
To aid human reading of different colour codes, colours are commonly represented in Hexadecimal using the RGB Red Green Blue system. For example the chart below shows how pure blue is represented using HEX, the HEX code for pure blue is #00 00 FF, meaning it has zero red components, zero green components and the maximum amount of Blue components.
To aid human reading of different colour codes, colours are commonly represented in Hexadecimal using the RGB Red Green Blue system. For example the chart below shows how pure blue is represented using HEX, the HEX code for pure blue is #00 00 FF, meaning it has zero red components, zero green components and the maximum amount of Blue components.
A brief colour chart for some of the other colours represented in hexadecimal.
Most software that allows you to manipulate images or colours will allow you to select colours by their HEX or RGB values.
Most software that allows you to manipulate images or colours will allow you to select colours by their HEX or RGB values.
Remember: Hex is used for our benefit to make it easy for use to see and work with, but the computer still deals with colour in binary format.
Image quality
The quality of an image depends predominantly of two factors, the amount of Pixels Per Inch (PPi) and the colour depth. The colour depth is determined by how many bits are used to represent each pixel, if 4 bits were used, most images would be grey scale, represented with only 2^4 (16) different shades possible to represent. HEX colour systems are commonly used and allow for 255 possible representations for each colour, Red, Green and Blue which equates to 8 bits used for each of the 3 colour, meaning 24 bit colour depth per pixel (2^24 = 16777216), giving over 16 million individual colours.
The two images below illustrate the difference in image quality where the same image is represented on an 8 x 8 PPi scale and a 16 x 16 PPi scale, both images are the same physical size however the 16 x 16 image is better quality because more resolution is greater.
Image quality
The quality of an image depends predominantly of two factors, the amount of Pixels Per Inch (PPi) and the colour depth. The colour depth is determined by how many bits are used to represent each pixel, if 4 bits were used, most images would be grey scale, represented with only 2^4 (16) different shades possible to represent. HEX colour systems are commonly used and allow for 255 possible representations for each colour, Red, Green and Blue which equates to 8 bits used for each of the 3 colour, meaning 24 bit colour depth per pixel (2^24 = 16777216), giving over 16 million individual colours.
The two images below illustrate the difference in image quality where the same image is represented on an 8 x 8 PPi scale and a 16 x 16 PPi scale, both images are the same physical size however the 16 x 16 image is better quality because more resolution is greater.
WHAT IS METADATA
Metadata is extra information that is within a picture file, as we learn from above the picture is actually just strings of binary, and within these string there is often extra data stored. This data often includes details of the device that took the picture and information such as the date the picture was taken. The amount of meta data has an impact on the actual file size of the image so calculating the file size from the image dimensions and bit depth might not be 100% accurate.
For more info on metadata CLICK HERE - BBC BITESIZE
For more info on metadata CLICK HERE - BBC BITESIZE
IMAGE FILE TYPES
There are many different type of images and each format has its unique attributes as follows:
JPEG or JPG : Joint Photographic Expert Group, a jpeg image has been compressed from its original size. The compression type is lossy, meaning it does loose some of its quality during compression. JPGs are good for photographs that require good quality images but a small data storage size, such as a photograph being used on a website.
Some other popular image file types include.
PNG: PORTABLE NETWORK GRAPHICS - Supports good quality graphics with 24BIT representation and designed to work well online through web-browsers.
GIF: GRAPHICS INTERCHANGE FORMAT - Normally not compressed and can retain features such as background transparency. The File can be large due to lack of compression. Compatible with many platforms.
BMP: BITMAP - Normally not compressed and therefore often maintain good quality but can take up more file space.
JPEG or JPG : Joint Photographic Expert Group, a jpeg image has been compressed from its original size. The compression type is lossy, meaning it does loose some of its quality during compression. JPGs are good for photographs that require good quality images but a small data storage size, such as a photograph being used on a website.
Some other popular image file types include.
PNG: PORTABLE NETWORK GRAPHICS - Supports good quality graphics with 24BIT representation and designed to work well online through web-browsers.
GIF: GRAPHICS INTERCHANGE FORMAT - Normally not compressed and can retain features such as background transparency. The File can be large due to lack of compression. Compatible with many platforms.
BMP: BITMAP - Normally not compressed and therefore often maintain good quality but can take up more file space.
CHECK YOUR KNOWLEDGE
What does a higher resolution achieve in a digital image?
A) It increases the file size without improving image quality.
B) It reduces the number of colors in the image.
C) It makes the image sharper and more detailed.
D) It reduces the size of the image on the screen.
EXPLAINATION
The correct answer is C: "It makes the image sharper and more detailed." A higher resolution increases the number of pixels per inch (PPI), resulting in a clearer and more detailed image.
.
Image Representation | The process by which a computer stores and displays visual data, such as images, using binary code.
Pixel | The smallest unit of a digital image, often represented as a tiny square of color. The image is made up of many pixels arranged in a grid.
Resolution | The number of pixels in an image, often expressed as width by height (e.g., 1920x1080). Higher resolution means more pixels, resulting in a sharper and more detailed image.
Color Depth | The number of bits used to represent the color of a single pixel. Higher color depth allows for more color combinations, improving image quality.
Bit Depth | Refers to the number of bits used for each color channel in an image. For example, 8-bit color depth uses 8 bits per color channel, resulting in 256 color values per channel.
RGB (Red, Green, Blue) | A color model where colors are represented by varying intensities of red, green, and blue. Each color is a combination of these three channels.
Palette | A set of colors available in an image. In limited color depth images, a palette is often used to represent colors more efficiently.
Compression | A method of reducing the file size of an image. Lossless compression retains all original data, while lossy compression sacrifices some detail to achieve a smaller file size.
Binary Code | The system of 0s and 1s used by computers to store all data, including image data. Each pixel’s color is stored as binary data.
File Format | The structure or type of an image file, such as JPEG, PNG, or BMP, which determines how the data is stored, compressed, and displayed.
Grayscale | An image that contains only shades of gray, represented by varying brightness levels from black to white. Grayscale images have lower color depth than full-color images.
High Resolution | An image with a large number of pixels, which results in more detail and clarity.
Low Resolution | An image with fewer pixels, which may appear blurry or pixelated when viewed at larger sizes.
True Color | A color depth of 24 bits, allowing for over 16 million color combinations and providing very high-quality color representation.
Pixel | The smallest unit of a digital image, often represented as a tiny square of color. The image is made up of many pixels arranged in a grid.
Resolution | The number of pixels in an image, often expressed as width by height (e.g., 1920x1080). Higher resolution means more pixels, resulting in a sharper and more detailed image.
Color Depth | The number of bits used to represent the color of a single pixel. Higher color depth allows for more color combinations, improving image quality.
Bit Depth | Refers to the number of bits used for each color channel in an image. For example, 8-bit color depth uses 8 bits per color channel, resulting in 256 color values per channel.
RGB (Red, Green, Blue) | A color model where colors are represented by varying intensities of red, green, and blue. Each color is a combination of these three channels.
Palette | A set of colors available in an image. In limited color depth images, a palette is often used to represent colors more efficiently.
Compression | A method of reducing the file size of an image. Lossless compression retains all original data, while lossy compression sacrifices some detail to achieve a smaller file size.
Binary Code | The system of 0s and 1s used by computers to store all data, including image data. Each pixel’s color is stored as binary data.
File Format | The structure or type of an image file, such as JPEG, PNG, or BMP, which determines how the data is stored, compressed, and displayed.
Grayscale | An image that contains only shades of gray, represented by varying brightness levels from black to white. Grayscale images have lower color depth than full-color images.
High Resolution | An image with a large number of pixels, which results in more detail and clarity.
Low Resolution | An image with fewer pixels, which may appear blurry or pixelated when viewed at larger sizes.
True Color | A color depth of 24 bits, allowing for over 16 million color combinations and providing very high-quality color representation.
1: Explain what is meant by the term ‘pixel’?
2: What is meant by the term ‘megapixel’?
3: What is meant by the term 'colour depth'?
4: Suggest two things that happen when you increase the colour depth.
5: What is meant by the term ‘image resolution’?
6: Suggest two things that happen when you increase the image resolution.
7: What is a Vector Graphic?
8: What is Meta Data
9: Give an example of information that could be stored in Meta data
2: What is meant by the term ‘megapixel’?
3: What is meant by the term 'colour depth'?
4: Suggest two things that happen when you increase the colour depth.
5: What is meant by the term ‘image resolution’?
6: Suggest two things that happen when you increase the image resolution.
7: What is a Vector Graphic?
8: What is Meta Data
9: Give an example of information that could be stored in Meta data
|
|
1.1 NUMBER SYSTEMS
☑ 1.1.1 WHY COMPUTERS USE BINARY
☑ 1.1.2 BINARY, HEX AND CONVERTIG BETWEEN NUMBER SYSTEMS
☑ 1.1.3 BENEFITS OF HEX
☑ 1.1.4 BINARY ADDITION AND OVERFLOW
☑ 1.1.5 BINARY SHIFTS
☑ 1.1.6 NEGATIVE NUMBER REPRESENTATION, TWO'S COMPLEMENT
1.2 COLOUR AND SOUND
☑ 1.2.1 HOW COMPUTERS REPRESENT TEXT
☑ 1.2.2 HOW COMPUTERS REPRESENT SOUND
➩ 1.2.3 HOW COMPUTERS REPRESENT IMAGES
1.3 FILE SIZE AND COMPRESSION
☐ 1.3.1 HOW STORAGE IS MEASURED
☐ 1.3.2 CALCULATING IMAGE AND SOUND FILE SIZE
☐ 1.3.3 PURPOSE OF COMPRESSION
☐ 1.3.4 LOSSY AND LOSSLESS COMPRESSION
EXTRAS
☐ END OF TOPIC REVIEW | COMING SOON
☐ TOPIC 1 KEY TERMINOLOGY
☐ REVISION FLIP CARDS
☐ TOPIC 1 ANSWERS
☐ TOPIC 1 TEACHER RESOURCES (CIE)
☑ 1.1.1 WHY COMPUTERS USE BINARY
☑ 1.1.2 BINARY, HEX AND CONVERTIG BETWEEN NUMBER SYSTEMS
☑ 1.1.3 BENEFITS OF HEX
☑ 1.1.4 BINARY ADDITION AND OVERFLOW
☑ 1.1.5 BINARY SHIFTS
☑ 1.1.6 NEGATIVE NUMBER REPRESENTATION, TWO'S COMPLEMENT
1.2 COLOUR AND SOUND
☑ 1.2.1 HOW COMPUTERS REPRESENT TEXT
☑ 1.2.2 HOW COMPUTERS REPRESENT SOUND
➩ 1.2.3 HOW COMPUTERS REPRESENT IMAGES
1.3 FILE SIZE AND COMPRESSION
☐ 1.3.1 HOW STORAGE IS MEASURED
☐ 1.3.2 CALCULATING IMAGE AND SOUND FILE SIZE
☐ 1.3.3 PURPOSE OF COMPRESSION
☐ 1.3.4 LOSSY AND LOSSLESS COMPRESSION
EXTRAS
☐ END OF TOPIC REVIEW | COMING SOON
☐ TOPIC 1 KEY TERMINOLOGY
☐ REVISION FLIP CARDS
☐ TOPIC 1 ANSWERS
☐ TOPIC 1 TEACHER RESOURCES (CIE)