Graphics

• Show understanding of how data for a bitmapped image are encoded

  • Use and understand the terms: pixel, file header, image resolution, screen resolution, colour depth, bit depth

• Perform calculations to estimate the file size for a bitmap image

• Show understanding of the effects of changing elements of a bitmap image on the image quality and file size

  • Use the terms: image resolution, colour depth

• Show understanding of how data for a vector graphic are encoded

  • Use the terms: drawing object, property, drawing list

• Justify the use of a bitmap image or a vector graphic for a given task

Sound

• Show understanding of how sound is represented and encoded

  • Use the terms: sampling, sampling rate, sampling resolution, analogue and digital data

• Show understanding of the impact of changing the sampling rate and resolution

  • Impact on file size and accuracy

Lesson 1 Task 1 Worksheet

There are a number of terms you must know for the exam:

Pixel

The word pixel stands for picture element.  it is the smallest amount of detail represented in an image.

Pixellation 

Pixellation  is caused by displaying a bitmap or a section of a bitmap at such a large size that individual pixels, small single-coloured square display elements that comprise the bitmap, are visible. Such an image is said to be pixellated.

File header

A file header is information that goes in front of the main information. In a bitmap image, before the individual pixel information is metadata such as image resolution, the x and y co-ordinates of the image, etc.  The file header also contains, depending on the file format, the ability to store other meta data such as where a picture was taken, who took it, the equipment used, etc.  However, bitmap (MBP) file format does not allow as much metadata as a JPEG image, for example.  A bitmap will have the file header (width, height, colour palette) and resolution only.

To calculate an bitmap image file size you need to know:

• • Total number of pixels (X * Y)

  • The image's colour depth (in bits).  E.g. 24-bit

You then multiply the number of pixels by the colour depth (that represents each pixel).  In the exam, you are not expected to take into account compression factors or file header information.  Should this ever be asked, it will be explained to you.

When dealing with bitmaps, it is important to understand resolution.  This great article explains resolution very well and an extract appears below.  If the preceding article gives too much information, a much pithier article can be found here, that explains the basics very well.

Camera resolution is measured in megapixels (meaning millions of pixels); both image file resolution and monitor resolution are measured in either pixels per inch (ppi) or pixel dimensions (such as 1024 by 768 pixels); and printer resolution is measured in dots per inch (dpi) (see below). In each of these circumstances, different numbers are used to describe the same image, making it challenging to translate from one system of measurement to another. This in turn can make it difficult to understand how the numbers relate to real-world factors such as the image detail and quality or file size and print size.

The bottom line is that resolution equals information. The higher the resolution, the more image information you have. If we’re talking about resolution in terms of total pixel count, such as the number of mega-pixels captured by a digital camera, we are referring to the total amount of information the camera sensor can capture, with the caveat that more isn't automatically better. If we’re talking about the density of pixels, such as the number of dots per inch for a print, we’re talking about the number of pixels in a given area. The more pixels you have in your image, the larger that image can be reproduced. The higher the density of the pixels in the image, the greater the likelihood that the image will exhibit more detail or quality.

The biggest question to consider when it comes to resolution is—How much do I really need? More resolution is generally a good thing, but that doesn't mean you always need the highest resolution available to get the job done. Instead, you should match the capabilities of the digital tools you’re using to your specific needs. For example, if you are a real estate agent who is using a digital camera only for posting photos of houses on a Web site and printing those images at 4 by 6 inches on flyers, you really don’t need a multi-thousand- dollar, 22-megapixel digital camera to achieve excellent results. In fact, a 4–6-megapixel point and shoot camera would handle this particular need, although having more image information would be beneficial in the event you needed to crop an image or periodically produce larger output.

The following is a video which gives you a background on how digital cameras work

Monitor Resolution

The primary factor in monitor resolution is the actual number of pixels the monitor is able to display. For desktop or laptop LCD displays there is a “native resolution” that represents the actual number of physical light-emitting pixels on the display, and this is the optimal resolution to use for the display. Any other setting will cause degradation in image quality.

The actual resolution is often described not just as the number of pixels across and down, but also with a term that names that resolution. For example, XGA (Extended Graphics Array) is defined as 1024 pixels horizontally by 768 pixels vertically. SXGA (Super Extended Graphics Array) is 1280 by 1024 pixels. There are a variety of such standard resolution settings. In general it’s best to choose a monitor with the highest resolution available so you can see as much of your image as possible at once. However, keep in mind that the higher the resolution, the smaller the screen’s interface elements will appear on your monitor.

Printer Resolution (not exam assessed - but helpful context)

For most bitmap images, the digital image’s defining moment is when ink meets paper. The quality is partly determined by the printer resolution. Once again, just to keep things confusing there are two numbers that are often labelled “print resolution”—output resolution and print resolution, and this is a major source of confusion. The marketing efforts of printer manufacturers only contribute to this confusion.

Output resolution in the image file is simply a matter of how the pixels are spread out in the image, which in turn determines how large the image will print and to a certain extent the quality you can obtain in the print.

Printer resolution is the measure of how closely the printer places the dots on paper. This is a major factor in the amount of detail the printer can render—and therefore the ultimate quality of the print. Note that the printer’s resolution is determined by the number of ink droplets being placed in a given area, not by the number of pixels in your image. Therefore, there won’t necessarily be a direct correlation between output and printer resolutions, because multiple ink droplets are used to generate the individual pixels in the image.

Each type of printer, and in fact each printer model, is capable of a different resolution. 

Vector graphics an image is composed from a toolbox of different shapes.  These shapes are called drawing objects.  The properties of these objects are stored as a set of mathematical equations, co-ordinates, etc.  The most useful aspect of vector graphics is that images can be easily scaled as each property can be recalculated. 

TheTeacher website has more information on vector graphics.

Drawing Object

The drawing object is the geometric shape which contributes towards the overall image.

Property

A property is information about a given thing.  In vector graphics, different drawing objects have different properties.  E.g. a circle would have information such as position (x,y), radius, line colour, etc..

Drawing List

The drawing list is the data that is saved to a particular vector file.  A drawing list is simply the set of properties that defines the drawing. These properties allow the image to be reconstructed later in any program that supports that file type.  The order of the drawing list dictates which objects appear "on top" of other objects.

• Vector images scale without file size increase / decrease

• Bitmap images scale resulting in file size increase / decrease

• Vector images scale without distortion to the image

• Bitmap images distort (pixellate) when scaling

• Bitmaps are better for photo editing

• Bitmaps require less processing power to display

Vector graphics are often used with simple images, text, etc.  Because they scale without distorting they are ideal for large image applications.  However, vector graphics cannot handle photorealism without an inextricable amount of work, therefore bitmap images are used when needing photorealism.  Additionally, monitors and printers ONLY work with raster (bitmap) images, so vector graphics must be converted to bitmap when displaying or printing onto paper.

The following is a list and brief comments of some specific file formats that are widely used for saving bitmaps, aside from JPEG.

In an analogue system, sound is captured by a transducer (perhaps a microphone) that produces an electrical signal that varies in proportion to the pressure created by the sound. That electrical signal can be transmitted or stored on a suitable medium (eg magnetic tape).

For the sound to be heard, the electrical signal must be used to recreate the original sound by vibrating a mechanical surface in a speaker. The term fidelity refers to the precision with which the original sound wave is recreated.

To help draw a real-world analogy, I have written a document that compares sound to measuring a cup of tea.  It can be found at the bottom of the page in the files section.

The Maths Of Sampling

An analogue frequency of 1000Hz is converted to a PCM signal by sampling at a frequency of 2000Hz (2000 samples per second). Each sample is encoded in 8 bits using PCM coding.

How many bytes of storage are required to encode 10 seconds of the analogue signal?

2000 samples taken each second.

10 x 2000 = 20 000 samples.

1 byte (8 bits) for each sample.

20 000 x 1 byte = 20 000 bytes.

Sampled Sound

Sampling Rate = The number of samples taken per unit time (usually seconds when measured in Hz).

Measured in Hz or KHz.

Sampling Resolution = The number of bits used to store each sample.

Measured in Kbps

How Often To Sample

Nyquist's theorem states that we must sample at twice the frequency of the highest signal in order not to miss meaningful changes in the original signal.

The bandwidth of an analogue signal is the difference between the highest frequency and the lowest frequency of the signal. This is the maximum frequency range of the signal. The Nyquist interval is one over twice the bandwidth.

For a signal with a frequency range of 3000Hz, sampling intervals should be no more than 1/6000 seconds apart.

44.1 kHz

44.1 kHz (44100 Hz) is the sampling rate of audio CDs giving a 20 kHz maximum frequency. 20 kHz is the highest frequency generally audible by humans, so making 44.1 kHz the logical choice for most audio material. High quality tape decks using metal tape, and medium quality LP equipment can reproduce 20 kHz (higher for top quality LP equipment, though some of this is harmonic distortion inherent in the medium). Note that the upper limit of human hearing falls rapidly with age. While people in their teens can hear 20 kHz, many older people cannot hear above 14.5kHz.

48 kHz

48 kHz (48000 Hz) is the sample rate used for DVDs so if you are creating DVD audio discs from your Audacity projects you may prefer to work with this setting. 

32 kHz / 14.5 kHz

• • 14.5 kHz is above the frequency limit of many medium quality sources, such as ferric cassette tape. On good tape decks, chrome tape can reproduce 18 kHz.

14.5 kHz cutoff also has a slight effect on speech, so 32k will give good quality speech recording, though not the best.

14.5 kHz is a little below FM radio bandwidth, so FM radio can be recorded with only a little quality loss.

32 kHz sample rate is thus good for:

• • cassette recordings from ferric stock

  • Speech

  • All other audio where smaller files than 44.1 kHz are desired with only slight compromise on sound quality.

22.05 kHz, 10 kHz

22.05 kHz (often lazily called "22 kHz") has been a reasonably popular sample rate for low bit rate MP3s such as 64 kbps in years past. Audio quality is significantly affected, with higher frequency content missing. With the general rise in the availability of large file storage space and faster data links, 22k is now of more limited use.

• • For speech recording where perceived quality is unimportant, but clarity must be maintained.

  • AM radio

  • To squeeze mp3 music onto floppy disk & very small mp3 players.

11.025 kHz / 5 kHz

11.025 kHz (often lazily called "11 kHz") gives 5 kHz maximum recorded frequency. Very poor sound quality.

8 kHz / 3.6 kHz

3.6 kHz matches the bandwidth of telephone sytems. Microcassette dictaphones have also used a similar bandwidth. 8 kHz sample rate is thus suitable for:

• • Telephone speech

  • Microcassette recording

  • To squash long speeches into small file sizes

Sound quality is terrible, with speech as clear as a mud bath. Any further drop in sample rate makes intelligibility a challenge. 

Sampling Resolution

A more accurate representation of the analogue signal can be achieved if more bits are used to store each sample. Measured in bits and often referred to as the bit depth, it describes how much information is captured for each sample.  This is why, when calculating the file size, we multiply the sampling frequency by sample resolution.  However, this calculation only gives the size per second, we then need to multiply by the length of the recording (in seconds) and finally, the number of channels (e.g. 2 for left and right).  

Do not confuse bit depth (aka sampling resolution) with bitrate.  Bit rate is the combination of sampling frequency and sampling resolution, often measured in kbps.

Alternative explanation (from the stereobus)

What is it that we’re measuring? Volume. Volume is represented by the height of the balls in the image. With each tick a new measurement of the volume is made. How do we describe the volume? Is it a range from 0 to 100? 0 to 2000? 0 to 1? The range of volumes that can be described is the bit rate. Now, in each of these examples, 0 means totally silent and 100, 2000, or 1, respectively, means as-loud-as-it-can-get. So the only difference between each of these ranges is not how loud the sound can be but how many different volumes can be described. We only have two choices for ‘0 to 1’, ie. is there a sound or not? But from 0 to 2000 we can have half volume (1000), quarter volume (500), or even somewhere in between (829). The higher the bitrate, the more accurately we can communicate exactly how loud the volume of the ‘real’ sound we want to describe is.

The bit rate can be thought of as how well the sound is described.

CD quality audio has 65,536 volumes to choose from for every sample that’s measured. That’s called 16-bit audio (because 2 to the 16th power is 65,536).

Compressed Audio

Compressed Speech

Data compression techniques are also used for encoding speech. These are different techniques to those used for compressing music.

Sound Mixing

Mixing sounds from different sources into a single file can be fun. Digital encoding of audio information makes this even easier than it was in the way back.

Sound Synthesis

Approximating real-world sounds using electrical equipment. Things like pianos aren't too bad. Some instruments are harder to emulate. MIDI (Music Information Digital Interface) stores no sound data, simply notes, duration and instruments. Very compact.

Streaming Audio

An audio streaming client (say, RealPlayer) starts receiving audio data from a remote location. This data is stored in a buffer. Once there are a few seconds of data in the buffer, the client begins playback from the buffer. As long as the buffer does not run out of data, the sound will play without pause.

Sound Editing

Representing sound in digital form allows for editing. This might mean removing background noise or specific frequencies. It might mean cropping or merging with other sounds.

The above section was taken from MultiWingspan's website.

• Fundamentals of Data Representation: Sounds

• Fundamentals of Data Representation: Analogue and digital

• Fundamentals of Data Representation: Sampled sound