1. Chap 1 Image fundamental

2. Trends Image processing techniques have developed from Gray-level processing to color processing 2-D processing to 3-D processing and reconstruction Static image processing to video Why use a computer to analyze images? What are the data to be analyzed? What does image analysis consist of?

3. Digitization

4. 2.4 Image sampling and quantization Convert the continuous sensed data to digital form Sampling Spatial transform: spatial coordinates(discrete locations) Quantization Amplitude transform: gray levels are converted to discrete values The quality of a digital image is determined to a large degree by the number of samples and discrete gray levels

5. Chapter 2: Digital Image Fundamentals

6. 2.4.2 Representing digital images The complete M  N digital image in the matrix form: f(x,y) Pixel, picture element A digital image use a traditional matrix A The number of gray levels L= 2 k The dynamic range of an image : the range of values spanned by the gray scale High contrast image : an image whose gray levels span a significant portion of the gray scale as having a high dynamic range The number, b, of bits required to store a digitized image is b=M  N  K

7. Chapter 2: Digital Image Fundamentals

8. 2.4.3 Spatial and gray-level resolution Sampling is the principal factor determining the spatial resolution Gray-level resolution: the smallest discernible range in gray level is the power of 2 due to hardware considerations The most common number: 8 bits Spatial resolution Sub-sampling Re-sampling Keep the number of samples constant and reduce the number of gray levels Reduce the number of bits while keeping the spatial constant Vary N and k simultaneously ISO reference curves If the number of bit are fixed, how to adjust the trade-off between spatial and gray-level resolution?

9. Chapter 2: Digital Image Fundamentals