Post on 17-Dec-2015
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?
2.4 Image sampling and quantization2.4 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
2.4.2 Representing digital images2.4.2 Representing digital images
The complete MN 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= 2k
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
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?