Image Processing and Analysis I

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Image Processing and Analysis I
Materials extracted from Gonzalez Wood and
Castleman
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A typical biomedical optics experiment
Detector
Image Processing
Light source
Intermediate Optics
Specimen
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Digital Image Processing
A process to extract information from image data
Preprocessing
Segmentation
Representation
Recognition
Interpretation, Modeling
Image Data Base Knowledge Base
Image Annotation, Compression, Storage/Retrieval
Image Acquisition
Problem Definition
Results
Display, Animation
Materials extracted from References
texts Gonzalez Woods, and Castleman
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Image Processing Example 1 Pap Smear
Squamous Cell Carcinoma
Benign Squamous Cells
One of the few histopathological tasks where
image recognition system is becoming commercial
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Image Processing Example 2 Breast X-Ray
The distinction between benign and malignant can
be difficult for breast x-ray Radiologist are
highly trained in image recognition Most
biomedical imaging today does not address
underlying molecular and cellular based
mechanisms
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Image Data Base Format and Data Base
Header
Monochrome
Color
Hyper-Data
1 bit binary
RGB R (8 bit) G (8 bit) B (8 bit)
8 bit
Data
16 bit
Gray Scale
32 bit
32 bits (float)
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Image Preprocessing histogram and contrast
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Image Preprocessing histogram equalization
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Image Preprocessing histogram and contrast
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Convolution and Image Processing
Recall the definition of convolution
Graphical explanation of convolution
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Convolution Theorem
where
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Image Preprocessing Noise Reduction,
averaging, low pass filter, median filter
Median Filter
Averaging M images reduce noise by sqrt(M)
Low Pass Filter
Replace center pixel value by the median value
from a nxn pixel neighorhood
3x3 kernel
5x5 kernel
Avg 30 Median 10
Avg by 2,8,16,32,128
Kernel 3,5,7,15,25
5x5 low pass vs median