1 / 81

1 IMAGING Seeing invisible things

1 IMAGING Seeing invisible things. Recap equations for wave travel Examine a range of digital images Explain what is meant by image resolution. Pixel. Pixels are the tiny building blocks from which a digital image is built. Resolution.

galeno
Download Presentation

1 IMAGING Seeing invisible things

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. 1 IMAGINGSeeing invisible things • Recap equations for wave travel • Examine a range of digital images • Explain what is meant by image resolution

  2. Pixel Pixels are the tiny building blocks from which a digital image is built.

  3. Resolution Smallest discernible feature or smallest detectable difference. Resolution = image dimension/number of pixels

  4. Current is kept constant so a record on the up and down motion is a record of the surface. Scanning tunnelling microscope.

  5. Ultrasound imaging • Explain principles of the technique • Calculate key parameters such as horizontal and vertical resolution, minimum pulse duration, maximum pulse rate

  6. Principles of Ultrasound Key things to know about: • How is it generated? • Why the need for short pulses? • Why the need for high frequency? What information do we gain from: • The pulse-echo times • The reflected intensity

  7. Ultrasound pulse sequence showing two pulses being sent out by the probe. The “listening time” is much longer than the duration of a pulse.

  8. 3-D ultrasound sends sound pulses in at different angles. A computer algorithm constructs a highly detailed image from the reflections. 4-D ultrasound is similar, except that the images are constructed rapidly to give almost real-time information.

  9. Ultrasound is also used to detect cracks in objects such as aeroplane components and rails. How does it work? Why is it preferable to using x rays?

  10. There are only 10 types of people in the world……. …..those who understand binary numbers …..and those who don’t. Can you explain this rather lame joke?

  11. Information in digital images • Explain how information is stored in digital images • Use binary arithmetic to work out the values stored for each pixel • Compute the amount of information in an image in bits and bytes

  12. Each Pixel is represented by a number

  13. Each pixel is assigned a byte of info = 28 = 256 alternatives = 256 levels of grey

  14. BinaryAll 0’s and 1’s

  15. BinaryAll 0’s and 1’s

  16. Bits and Bytes One Bit of information = 0 or 1 (two possibilities) Eight Bits of information = 256 possibilities. (8 bits = 1 byte) HOW? There are 256 alternative arrangements of 8 bits. (each bit is either 1 or 0)

  17. There is 0/1 alternative for each position One 0/1 choice = One bit In 8 bit data there are eight 0/1 alternatives Eight bits = eight 0/1 choices = One byte There are 28 = 256 alternatives or 0-255 Number of alternatives = 2I Where I is the number of bits. e.g. 16 bit computer uses 216 = 65536

  18. Each pixel is assigned a byte of info 00000001 = A 00000010 = B . . . 10010010 = &

  19. Bits and Bytes N = number of alternatives l = number of bits N= 28 = 256 In general: N = 2l log2N= l

  20. Amount of data in image = no. of pixels x bits per pixel

  21. Questions: 120S – Logarithms and Powers The response of the eye (and ear) to light (and sound) intensity is logarithmic not linear. A logarithm is just another name for the power (or exponent or index – lots of different names for the same idea!) that the constant ratio is raised to. 1.We can choose convenient ratios to consider: take a constant ratio of x 10. Write out a series of intensity values starting with 1 with this constant ratio property. 2. If you haven't done so, repeat question 1, writing out the series using scientific notation and powers of ten. 3. What is happening to the power of ten (its index), or logarithm to base 10? The base is just the initial constant ratio we chose to work with; any number will do. (Base 2 gives binary, base 10 gives log10 , base e (e = 2.718...) gives the natural loge (written ln).

  22. Questions: 120S – Logarithms and Powers 4. Using your calculator, record log10 of the series 1, 10, 100, 1000, 10000 etc. What do you notice? 5. Sketch a graph of the series of intensities plotted on the y-axis, against the powers of ten or log10 plotted on the x-axis. This graph is logarithmic in shape (we say it grows exponentially). Now plot the graph on a log scale (non-linear), i.e. log10 (series) on y-axis against the powers of ten on the x-axis. What has the log scale done to the exponentially growing data? You will use log scales for representing quantities that vary enormously, and for testing for logarithmic or exponential variations.

  23. Questions: 120S – Logarithms and Powers 6. If you have followed these steps so far, you have in fact learnt to master the scale for the measurement of sound intensity ratios, the bel scale (after Alexander Graham Bell) where: number of bels = log10 (I2 / I1 ) or more commonly the sound level in decibels (1 dB = 0.1 B) is given by number of decibels = 10 log10 (I2 / I1) A sound that is on the threshold of audible intensity is 10-12 W m-2 (like hearing a pin drop). This is taken as the baseline intensity I1. A painful sound (like a jet taking off) has an intensity of about 10 W m-2. What is the sound level of the jet in bels and dB?

  24. Image processing • Process a range of digital images to extract the maximum amount of useful information • Explain how the processing algorithms work

  25. Image processing algorithms Smoothing Noise removal Edge detection Change brightness Change contrast

  26. Image processing algorithms For each of the image processing algorithms: Describe its effect on an image. Explain how the algorithm operates on the data. Describe a situation where it might be useful. Discuss any drawbacks of the algorithm. • Smoothing • Noise removal • Edge detection • Change brightness • Change contrast The “Mars Face”

  27. Smoothing out sharp edges Replace each pixel by the mean of it and its eight neighbours

  28. Resulting in....

  29. Image before sharpening

  30. Image after sharpening

  31. Removing Noise Replace each pixel by the median of its value and those of its neighbours

  32. Resulting in...

  33. Finding Edges Laplace Rule Subtract the N, S, E and W neighbours from 4x the value of each pixel.

  34. Finding Edges Laplace Rule Result if there is an edge. Subtract the N, S, E and W neighbours from 4x the value of each pixel.

  35. Finding edges with the Laplace Rule If there is no edge but a gradient then the Laplace rule simply smooths the data

  36. Improving Contrast How might we make image brighter? How might we improve the contrast? Decimal numbers of image

  37. Improving Contrast Adding fixed positive value makes image brighter +4 x2 Multiplying by fixed value increases contrast and makes brighter.

  38. A histogram analysis showing how many pixels there are in an image that have a particular number of pixel values is very useful in explaining how the contrast and brightness algorithms work………………….

  39. Starter: Match up the image processing technique with the algorithm that describes how it is applied to the data A Smoothing B Noise removal C Edge detection D Change brightness E Change contrast • Subtract N,S,E,W neighbours from 4 times value of pixel. • Multiply all pixel values by a constant factor. • Add a fixed value to all pixel values. • Replace each pixel value by the median of its value and those of its neighbours • Replace each pixel value by the mean of its value and those of its neighbours

  40. Making images using lenses • Recap relationship between light rays and waves • Investigate properties of converging lenses • Solve problems using 1/v = 1/u+1/f

  41. The King of all Imagers: The Eye. 100 million rods 5-10 photons are required to trigger a response.

More Related