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DIGITAL IMAGE PROCESSING DIGITAL IMAGE PROCESSING Titipong Keawlek M.Sc.(Radiological Sciences) Department of Radiological Technology ,Naresuan University DIGITAL IMAGE PROCESSING DIGITAL IMAGE PROCESSING History of Digital Image Processing - Examples of Fields that Use Digital Image Processing - Fundamental Steps in Digital Image Processing - Components of an Image Processing System Digital Image Fundamentals - Elements of Visual Perception - Light and the Electromagnetic Spectrum - Image Sensing and Acquisition - Image Sampling and Quantization DIGITAL IMAGE PROCESSING DIGITAL IMAGE PROCESSING Changing Image Characteristics with processing Contrast Adjustment by Digital Processing - LUT ( Look Up Table) - Windowing Using Digital Processing to change Image Contrast - LUT Described by Graphs - LUT Curve - Selection of LUTS Processing to Increasing Image Contrast - Processing a chest Image - Brightness Scale Inversion Digital Image Windowing - Effect of Changing the Window Level - Enhancing Visibility of Detail In medical Image History of Digital Image Processing

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DIGITAL IMAGE PROCESSINGDIGITAL IMAGE PROCESSING

Titipong Keawlek M.Sc.(Radiological Sciences)Department of Radiological Technology ,Naresuan University

DIGITAL IMAGE PROCESSINGDIGITAL IMAGE PROCESSING

• History of Digital Image Processing

- Examples of Fields that Use Digital Image Processing

- Fundamental Steps in Digital Image Processing

- Components of an Image Processing System

• Digital Image Fundamentals

- Elements of Visual Perception

- Light and the Electromagnetic Spectrum

- Image Sensing and Acquisition

- Image Sampling and Quantization

DIGITAL IMAGE PROCESSINGDIGITAL IMAGE PROCESSING

•Changing Image Characteristics

with processing

•Contrast Adjustment by Digital

Processing

- LUT ( Look Up Table)

- Windowing

•Using Digital Processing to change

Image Contrast

- LUT Described by Graphs

- LUT Curve

- Selection of LUTS

•Processing to Increasing Image Contrast

- Processing a chest Image

- Brightness Scale Inversion

•Digital Image Windowing

- Effect of Changing the Window Level

- Enhancing Visibility of Detail

In medical Image

History of Digital Image Processing

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Figure 1.1

One of the first applications of digital images was in the newspaper industry, when pictures were first sent by submarine cable between London and NewYork.

early 1920s

Figure 1.2

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In parallel with space applications, digital image processing

techniques began in the late 1960s and early 1970s to be used in medical

imaging, remote Earth resources observations, and astronomy.

computerized tomography (CT)

Other images used in industry,medicine,and the biological sciences.

Examples of Fields that Use Digital Image Processing

-Gamma-Ray Imaging-X-Ray Imaging-Imaging in the Ultraviolet Band-Imaging in the Visible and Infrared Bands-Imaging in the Microwave Band-Imaging in the Radio Band-Examples in which other imaging modalities are used

Examples of fields that use DIPGamma-Ray Imaging

Examples ofgamma-ray imaging. (a) Bone scan. (b) PET image. (c) Cygnus Loop. (d) Gamma radiation (bright spot) from a reactor valve.

abcd

X-ray Imaging

Examples of X-ray imaging. (a) Chest X-ray. (b) Aortic angiogram. (c) Head CT. (d) Circuit boards. (e) Cygnus Loop.

acdbe

Examples of ultraviolet imaging.(a) Normal corn.(b) Smut corn.(c) Cygnus Loop.

abc

Imaging in the Ultraviolet Band

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Imaging in the Visible and Infrared Bands

a b cd e f

Examples of light microscopy images. (a)Taxol (anticancer agent), magnified 250µ. (b) Cholesterol—40µ. (c) Microprocessor—60µ. (d) Nickel oxide thin film—600 µ. (e) Surface of audio CD—1750µ. (f) Organic superconductor—450µ.

TABLE : Thematic bands in NASA’s LANDSAT satellite.

Imaging in the Visible and Infrared Bands

Imaging in the Visible and Infrared Bands

LANDSAT satellite images of the Washington, D.C.area. The numbers refer to the thematic bands in Table 1.1. (Images courtesy of NASA.)

Multispectral image of Hurricane

Andrew taken byNOAA GEOS (Geostationary Environmental Operational Satellite)sensors.

Imaging in the Visible and Infrared Bands

Infrared satellite images of the Americas.The small gray map is provided for reference.

Imaging in the Visible and Infrared Bands

Infrared satellite images of the remaining populated part of the world.The small gray map is provided for reference.

Imaging in the Visible and Infrared Bands

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Some examples of manufactured goods often checked using digital image processing.

(a)A circuit board controller.(b) Packaged pills.(c) Bottles.(d) Bubbles in clear-plastic product.(e) Cereal.(f) Image of intraocular implant.

Imaging in the Visible and Infrared Bands

abcdef

Imaging in the Microwave Band

Examples of imaging in the visual spectrum.

(a) Thumb print.(b) Paper currency. (c) and(d).

Automated license plate reading.

Spaceborne radar image of mountains in southeast Tibet.

Imaging in the Microwave Band Imaging in the Radio BandAs in the case of imaging at the other end of the spectrum (gamma

rays), the major applications of imaging in the radio band are in medicine and astronomy.

MRI images of a human (a) knee, and (b) spine.

Imaging in the Radio Band

Images of the Crab Pulsar (in the center of images) covering theelectromagnetic spectrum.

The last image to the right in Fig. shows an image of the Crab Pulsar inthe radio band.

Also shown for an interesting comparison are images of thesame region but taken in most of the bands discussed earlier.

*Note that each image gives a totally different “view” of the Pulsar.

Examples in which Other Imaging Modalities Are Used

I. Acoustic imaging

-Hundreds of Hertz

Geological exploration

-Millions of Hertz - ultrasound

Industry

Medicine

II.Electron microscopy

III.Synthetic (computer generated) imaging

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I.Ultrasound- Mineral or Oil exploration

Examples in which Other Imaging Modalities Are Used

Cross-sectional image of a seismic model.The arrow points to a hydrocarbon (oil and/or gas) trap.

Examples in which Other Imaging Modalities Are Used

Examples of ultrasound imaging. (a) Baby.(b) Another view of baby.(c) Thyroids.(d) Muscle layers showing lesion.

a bc d

I.Ultrasound

A transmission electron microscope (TEM)

A scanning electron microscope (SEM),

Electron microscopes are capable of very high magnification.While light microscopy is limited to magnifications on the order 1000 x, electron microscopes can achieve magnification of 10,000x or more.

II.Electron microscopy

Examples in which Other Imaging Modalities Are Used

(a) 250x SEM image of a tungsten filament following thermal failure.(b) 2500x SEM image of damaged integrated circuit. The white fibers are oxides resultingfrom thermal destruction.

III.Synthetic imaging

Examples in which Other Imaging Modalities Are Used

Fractals

3D objects

Digital Image Fundamentals

Elements of Visual PerceptionStructure of human eyes

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Receptors: Cones and Rodsfull of receptors ‘cones’, sensitive to colorsfull of receptors ‘rods’,insensitive to colors,sensitive to

intensity

Structure of human eyesDistribution of Cones and Rods on retina

Structure of human eyes

Rods are highly responsive to light, but see only a single band of

light, and therefore cannot discriminate color

Peripheral Vision: (rods)Responsible for perception under low- intensity Light.Low spatial resolution

Higher sensitivity to temporal variationsLess sensitive to color

Peripheral Vision: (rods)

Cones are less responsive, but see three distinct color spectral

bands of light,enabling color vision.

Fovea Vision: (cones)

-Responsible for perception under high intensity light

-Very high spatial resolution (near 1 min. visual acuity)

-Less sensitive to temporal variations

-Highly sensitive to color

Image formation in the eye

The focal length of the eye various from 14 mm to 17mm.

Brightness adaptation and discrimination photopic scotopic

true intensity

intensity perceivedby human eye

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The solid line shows: intensity perceived by human is not

proportional to true intensity.

Human eye does not respond to such a large dynamic

range simultaneously, it adapts gradually.

It’s instant discriminability is as narrow as the curve Ba to Bb

when adjusted to this range

Weber ratio (measure of adaptive discriminability)

Weber ratio is ∆IC/I, where

I : the background intensity∆IC : just noticeable difference(JND) between a circle and its background

- Large Weber ratio indicates better discriminability

-Weber ratio (discriminability) decrease with intensity (brightness)

Mach bands (1865)

-The true change in intensity is

a step function, as shown by solid line.

-Human eye tends to increase

the contrast at the edge of two steps

by undershooting and overshooting, as

indicated by dash line.

-This phenomena is called the

‘Mach bands’.

Light and its spectrum

The wavelength of visible light is about 0.43~0.79 µm

Image sensing and Acquisition

Line camera

Line camera is used when the object moves (rotate) along the

other direction to complete a 2-D scanning.

Field camera

Field camera is usually carried by an X-Y table to complete a

2-D scanning.

The scene that a field camera capture in each shoot is called

a ‘field of view (FOV)’.

Image Sampling and QuantizationSampling and quantized using 8-bits grey level

The image is sampled (with fixed spatial resolution/frequency) and

quantized into 8-bits grey level, then the grey level (of the image) is

recorded as a matrix with the coordinate system shown on the upper right.

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Sampling down

Image Sampling and Quantization

Sampling down from 1024×1024 to 32×32

1024×1024 512×512 256× 256

128×128 64× 64 32×32

Aliasing and Moiré pattern

Image Sampling and Quantization

Aliasing: high frequency pattern mis-interpreted as low frequency

pattern,it occur when the image is sampled at too low a frequency.

To avoid aliasing, the Nyquist sampling theorem has to be obeyed:sampling frequency ΩS ≥ 2ΩP maximum frequency in the pattern

Moiré pattern occur when two identical periodic pattern are

overlapped with an intersection angle as shown below

One set of periodic lines can be perceived as the sampling pulses train to modulate the other pattern of periodic lines.

Ωs = Ω p< 2Ω p, aliasing occur, a pattern at a lower frequency(periodic horizontal lines) occurs called Moiré pattern.

Image Sampling and Quantization

Digital Image Digital Image ProcessingProcessing

In medical ImageIn medical Image

DIGITAL IMAGE PROCESSINGDIGITAL IMAGE PROCESSING

ขอไดเปรยบอยางหนงในการใชภาพดจทลในทางการแพทย คอ สามารถเปลยนแปลงภาพโดยใชคอมพวเตอรได

สามารถเลอก และปรบลกษณะของภาพ เพอใหคณภาพดขนและสามารถมองเหนรายละเอยดของภาพไดดทสด

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CHANGING IMAGE CHARACTERISTICS WITH CHANGING IMAGE CHARACTERISTICS WITH PROCESSINGPROCESSING

สงสาคญทปรบเปลยนไดในภาพดจตอล ม 3 อยาง คอ

- การลด Image noise

- การเพม Visibility ของ Detail ภาพ

- Adjust และ optimize Image Contrast characteristics

CONTRAST ADJUSTMENT BY CONTRAST ADJUSTMENT BY DIGITAL PROCESSINGDIGITAL PROCESSING

วธทใชสาหรบ Contrast Characteristics ของภาพมหลายวธ ยกตวอยางเชน

- Look up Table (LUT) Processing

- Windowing

ทงสองวธน จะใชไดดในการสรางภาพดจทลทางการแพทย

CONTRAST ADJUSTMENT BY CONTRAST ADJUSTMENT BY DIGITAL PROCESSINGDIGITAL PROCESSING

USING DIGITAL PROCESSING USING DIGITAL PROCESSING TO CHANGE IMAGE CONTRASTTO CHANGE IMAGE CONTRAST

ในภาพจะประกอบดวย pixel ขนาดเลกๆ ซงบรรจคาขอมลทตางกนของเนอเยอ ทาใหเกดเปนภาพ

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USING DIGITAL PROCESSING USING DIGITAL PROCESSING TO CHANGE IMAGE CONTRASTTO CHANGE IMAGE CONTRAST

Look up tables (LUT) are data stored in the computer that is used to substitute new values for each pixel during the processing.

The image consist of a background area and a small square object in the center.

USING DIGITAL PROCESSING USING DIGITAL PROCESSING TO CHANGE IMAGE CONTRASTTO CHANGE IMAGE CONTRAST

จากรป Low Contrast บรเวณ background area มคา pixel values เทากบ 40 สวน center area มคา pixel values เทากบ 30∴Numerical contrast (the object relative to the background) ม

คาแตกตางกนเทากบ (40-30=10).

USING DIGITAL PROCESSING USING DIGITAL PROCESSING TO CHANGE IMAGE CONTRASTTO CHANGE IMAGE CONTRAST

เมอตองการปรบภาพใหเปลยนแปลงคาขอมลภาพ โดยใช LUT ดงตวอยาง

USING DIGITAL PROCESSING USING DIGITAL PROCESSING TO CHANGE IMAGE CONTRASTTO CHANGE IMAGE CONTRAST

The processing uses a LUT that substitutes a 90 for a 40 and a 10 for a 30. The effect of this is to increase the image contrast (90-10=80).

เราสามารถทาการเลอกใช LUTs ทตางกนได ขนอยกบลกษณะspecific contrast characteristics ของสวนทตองการวนจฉย

USING DIGITAL PROCESSING USING DIGITAL PROCESSING TO CHANGE IMAGE CONTRASTTO CHANGE IMAGE CONTRAST

LUT เปนตวบงชใหเหนความแตกตางของคาขอมลตวเลข (Value) ทใชแทน ในแตละ pixel ทาใหเกดเปนภาพทตางกน

LUT DESCRIBED BY GRAPHSLUT DESCRIBED BY GRAPHS

กราฟแสดงความสมพนธระหวาง คา pixel values ตงตน กบคา pixel values ใหม

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LUT DESCRIBED BY GRAPHSLUT DESCRIBED BY GRAPHS

จากกราฟจะเหนวากราฟมลกษณะเปน simple straight-line หรอ linear graph หากเลอกใช LUT น การแทนคา values จะมคาเทาเดมกบ original image pixel value. ลกษณะภาพจะเหมอนกบภาพตนฉบบ

LUT CURVELUT CURVE

แตถาหากเลอก LUT processing ทใชในการเปลยนแปลงภาพ โดยการแทนคาดวยคาทตางจากคาเดม

LUT CURVELUT CURVE

Radiographic film characteristic (H & D) curve

*ประโยชนจากการใช digital processing คอ สามารถเลอก คา parameter ทจะทาใหไดภาพทม contrast characteristics แตกตางกน

จะไดภาพทม High Contrast

SELECTION OF LUTSELECTION OF LUT

ลกษณะกราฟ ทแตกตาง ทาให Pixel Values ทตางกน

SELECTION OF LUTSELECTION OF LUT

จากกราฟ ความชน ของกราฟทมคามาก จะทาให contrast เพมขน

ความชน ของกราฟทมคานอย จะทาให contrast ลดลง

(เมอ ความชนนอยกวา 45องศา)

SELECTION OF LUTSELECTION OF LUT

แตถา ความชน เทากบ 45 องศา คา contast จะไมเปลยนแปลง

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SELECTION OF LUTSELECTION OF LUT

เราควรจะตงคาทเหมาะสมกบ อวยวะทจะถาย เชน chest ,extremetry และอนๆ

PROCESSING TO INCREASE PROCESSING TO INCREASE IMAGE CONTRASTIMAGE CONTRAST

High ContrastLow Contrast

แตการใช LUT แบบ high contrast จะทาใหปอดมคาความดามากเกนไป ฉะนนการใช LUT แบบนจงไมเหมาะกบ การถายภาพ Chest

PROCESSING A CHEST IMAGEPROCESSING A CHEST IMAGE

BRIGHTNESS SCALE BRIGHTNESS SCALE INVERSIONINVERSION

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DIGITAL IMAGE DIGITAL IMAGE WINDOWINGWINDOWING

Windowing is the process of selecting some segment of the total pixel value range (the wide dynamic range of the receptors)

and then displaying the pixel values within that segment over the full brightness (shades of gray) range from white to black.

Contrast will be visible only for the pixel values that are within the selected window.

All pixel values that are either below or above the window will be all white or all black and display no contrast.

The person controlling the display can adjust both the center and the width of the window.

The combination of these two parameters determine the range of pixel values that will be displayed with contrast in the image.

EFFECT OF CHANGING EFFECT OF CHANGING THE WINDOW LEVELTHE WINDOW LEVEL

Compared to the limitations of images displayed on film where the full range of exposure is displayed in one image and cannot be changed.

With windowing we can create many displayed images, each one "focusing on" a specific range of pixel values.

The advantages of windowing is that it makes it possible to display and enhance the contrast in selected segments of the total pixel value range.

EFFECT OF CHANGING EFFECT OF CHANGING THE WINDOW LEVELTHE WINDOW LEVEL

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When the window is set to cover the lower segment of total pixel value range, we see good contrast in the lighter areas like the medistimum.

EFFECT OF CHANGING EFFECT OF CHANGING THE WINDOW LEVELTHE WINDOW LEVEL

Setting the window to the higher segment produces good contrast in the darker areas like the lungs.

EFFECT OF CHANGING EFFECT OF CHANGING THE WINDOW LEVELTHE WINDOW LEVEL ENHANCING VISIBILITY OF DETAILENHANCING VISIBILITY OF DETAIL

The Blurred Mask Subtraction is often used, especially in digital radiography, to enhance the visibility of detail in certain clinical procedures.

This process does not un-blur an image and recover detail that was completely lost because of blurring from the focal spot, motion, and the receptor.

What it does do is increase the visibility (contrast) of some objects, especially where the visibility of the objects is somewhat limited by large area contrast as in chest imaging.

ENHANCING VISIBILITY OF DETAILENHANCING VISIBILITY OF DETAIL

Question ?

ENHANCING VISIBILITY OF DETAILENHANCING VISIBILITY OF DETAIL

The process consist of two distinct steps.

1st step

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A common form of digital processing that can be used to produce a blurred image is just by replacing each pixel value with the average of the pixel values in it's neighborhood.

ENHANCING VISIBILITY OF DETAILENHANCING VISIBILITY OF DETAIL

blurred mass image.

1.The original image contains the general large-area contrast background plus some detail.

We now have two images.

2.The blurred mask image contains only the large-area contrast background

Original Blurred mask image

The final step is where the computer subtracts the blurred mask image (actually some fraction of it) from the original image.

ENHANCING VISIBILITY OF DETAILENHANCING VISIBILITY OF DETAIL

This process reduces the large-area contrast background in relation to the contrast of the detail.

The result is that the contrast and visibility of the detail (small objects and structures) is enhanced.

ENHANCING VISIBILITY OF DETAILENHANCING VISIBILITY OF DETAIL