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Chapter 5 Digital Image Processing Fundamentals. Time Why would you want to? How do you time stuff? What kinds of API’s are available for timing.

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Presentation on theme: "Chapter 5 Digital Image Processing Fundamentals. Time Why would you want to? How do you time stuff? What kinds of API’s are available for timing."— Presentation transcript:

1 Chapter 5 Digital Image Processing Fundamentals

2 Time Why would you want to? How do you time stuff? What kinds of API’s are available for timing.

3 Why time stuff? Image Processing can be slow. To measure performance improvements. WHO CARES? –User cares. Users notice if a program runs slow. –Hardware people ( mission critical response times). –Medical Application. –Security (luggage) face recognition.

4 How do you time stuff? stop-watch subroutines (date functions) to get time. java.util.date (perhaps to within a second) Hardware interface Processor clock (milliseconds).

5 To automate timing.. Need framework for benchmarking. Framework – set of related classes design to solve a problem. java 4 programmers I have: –utils.Timer

6 How do I use the Timer? public static void main(String[] args) { Timer t = new Timer(); t.mark(); double j = Math.PI; for (int i=0; i < 100000000; i++){ j = j / Math.E; j = Math.PI; } t.record(); float f = t.getElapsedTime(); t.report(); }

7 How do you make timing meaningful? What was done in the given time? What environment ran the experiment? –What machine was used? –How did much memory did you have? –What processor was there? –What speed did the processor run at? –What compiler switches did you use?

8 How do I find out about the machine? System.properties!

9 Learning Goals The human visual system Digitizing images Display of Images

10 Trading an eye for an ear

11 An eye is a Multi-mega pixel camera It has a lens (adjustable zoom) It has an automatic f-stop (iris 2-8 mm) It has a sensor plane (100 million pixels) The sensor has a transfer function senstive to mesopic range; 380 to about 700 nm

12 The eyes have a USB2 data rate! 250,000 neurons in the optic nerve variable voltage output on EACH nerve 17.5 million neural samples per second 12.8 bits per sample 224 Mbps, per eye (a 1/2 G bps system!). Compression using lateral inhibition between the retinal neurons

13 Response curves Eye has Gaussian response to light. Gives rise to biologically motivated image processing

14 Quantization of an Image Computers use digital cameras -> quantization

15 Delta-function

16 Sampling an Image

17 Sampling=convolution w pulse train

18 Quantization Error is visible

19 Displays Color Monitors are made for people


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