digital image processingqil.uh.edu/dip/media/cosc6380/lecture_-_1_iojmhqx.pdf · 2021. 1. 21. ·...

Digital Image ProcessingCOSC 6380/4393

Lecture – 1Jan 19th, 2021

Slides from Dr. Shishir K Shah and Frank (Qingzhong) Liu

Digital Image ProcessingCOSC 6380/4393

• Instructor– Pranav Mantini– Email: [email protected]– Office: Zoom Meetings (http://qil.uh.edu/dip/meeting/)– Office Hours: TTH 11:00 AM – 12:00 PM

• TA – Office: Zoom Meetings (http://qil.uh.edu/dip/meeting/)– Zhenggang Li ([email protected])

• Office Hours: Fri 1:00 PM – 3:00 PM– Kadhija Khaldi ([email protected])

• Office Hours: Wed/Fri 10:00 AM – 11:00 AM– Poonam Beniwal ([email protected])

• Office Hours: Wed 2:00 PM – 3:00 PM

http://qil.uh.edu/dip/meeting/http://qil.uh.edu/dip/meeting/

Introduction to the course

• Class Time & Location– Zoom Meetings (http://qil.uh.edu/dip/meeting/)– Tu, Th: 08:30 AM – 10:00 AM– http://qil.uh.edu/dip

• Grading – Assignments: 60% – Exam: 20% – Quizzes: 20%

http://qil.uh.edu/dip/meeting/http://qil.uh.edu/dip

• Individual Assignments – ~4 to 6 Assignments - 60% – Implementation, Python, OpenCV Libraries

• Mid-term Exam – 20%• Quizzes - 20%

– Biweekly (once every 2 weeks)– Include only content from past two weeks– No quiz during midterm week

Graduate Vs. Undergraduate

• This is a combined section.• The two sections are graded separately based on individual

statistics.• Higher expectation for Graduate section

– Different or extended quizzes, midterms, and assignments

Logistics• Late policy for Assignments:

– Late by 1 day - 25% off the grade – Late by 2 days - 50% off the grade – Late by more than 2 days – No Credit

• Late policy for quizzes/midterm:– Late submission – No Credit

• Collaboration policy: – Discussing assignments with each other is allowed, but coding must be done

individually – Discussing Quizzes and midterm is not allowed– Coding policy: using online code or other students/researchers’ code is not allowed. – Posting questions on online forums (Chegg.com, etc.) is not allowed

Plagiarism

• The entire assignment/project will not be graded, zero score will be awarded, and reported to the department.

• Tips:– Do not share code/report– Do not share snippets of code– Do not share algorithms (but you can share ideas)– Do not copy from online sources– Ideally, your code should not leave your computer/repo except for

submission– Cite sources properly for reports

Interim grading policy

• No interim grading policy this term (‘S’ or ‘NCR’) for either undergraduate or graduate students.

TEXTBOOK

• Digital Image Processing, 2nd Edition/3rd Edition, R. C. Gonzales and R. E. Woods, Prentice Hall.

RECOMMENDED BOOKS

• Digital Image Processing, 2nd Edition/3rd Edition, R. C. Gonzales and R. E. Woods, Prentice Hall.

• Digital Image Processing, K. R. Castleman, Prentice Hall, 1996.• Image Processing, Analysis, and Machine Vision, Milan Sonka,

Vaclav Hlavac, and Roger Boyle, Pacific Grove, 1999.• Fundamentals of Digital Image Processing, Anil K. Jain, Prentice

Hall, 1989.• The Image Processing Handbook, John C. Russ, CRC Press,

2002.

Course Expectations

1. Lectures (Required)1. Attend Lecture meeting or Watch video 2. Ask questions

2. Submit quizzes via Blackboard (Required)3. Submit midterm via Blackboard (Required)4. Submit assignments via Github (Required)5. Attend Office hours (Optional)

Class Website

http://qil.uh.edu/dip

http://qil.uh.edu/dip

Accessing VideosGo to class website: qil.uh.edu/dip

Accessing Videos

Click for video

Watch Videos

Video player

Forum and Discussion

Post question

Scroll down

Post Questions

Post question

Scroll down

:

Post QuestionPost question by logging in using a gmail account

Post question as anonymous

Post question using you name

(Preferred – it makes it easy to answer questions)

Attending Meetings

1. Two types of meetings:1. Lecture meeting: Discuss course topics, address any questions from

videos, and answer other questions if time permits.2. Office hours: Answer questions, help with assignments, etc. Please

remember these meetings are not completely one to one. Please communicate with the TA and setup separate meeting with TA if you need to discuss something alone. (For example grades etc.)

Meeting

Attend Meeting• Three ways

– Via phone1. Call +1-346-248-77992. Enter Access Code (See meeting page for specific access code)

– Via computer1. Follow the link.

1. No need to signup2. On windows it might install a plugin, accept and install3. On Linux/mac just follow the link and you should be able to enter the meeting4. Allow necessary permission in the browser to access the mic and audio

– Via mobile App1. Download app2. Enter meeting number3. Enter Passcode

Attend Meeting

1. You can log-in ahead and wait for the meeting to start.2. Make sure your mic is in mute when you enter the meeting.

1. These meetings are like classrooms, to minimize background noise make sure to enter the meeting with your mic in mute, and continue to keep in mute.

2. You can unmute when you have a question. We will figure out the details as we go along.

Pre-Introduction

• Example: Measure depth of the water in meters at a certain pier

• Take measurements randomly over time

H 18 22 4 9 17 7 21 3 19 1 12 13 15 11 6 16 23 10 8 2 20 0 14 5

D 2 1.5 2.4 1.5 2.2 1.75 1.5 2.5 1.75 2.25 2 2.25 2.5 1.75 2 2.4 1.75 1.5 1.5 2.4 1.5 2 2.4 2.25

Pre-Introduction


• Another representation

H 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

D 2 2.2 2.4 2.5 2.4 2.25 2 1.75 1.5 1.5 1.5 1.7 2 2.25 2.4 2.5 2.4 2.25 2 1.75 1.5 1.5 1.5 1.75

Pre-Introduction


• Yet another representation (chart: a graphical representation of data)

Pre-Introduction


• Yet another representation• Image as a mode/format to

convey information; for human consumption, for further processing, and etc.

Why an Image?

Why an Image?

• Psychology– Vision is how we experience the world– ~ 50% of cerebral cortex is for vision

Image Processing

• How do I acquire images that capture information?– Image Acquisition

• How do I process and present the acquired image?– Filtering and image enhancement– Image restoration– Color image processing

• How do we store and transfer images efficiently?– Compression

• Can we understand what is the information/content in the image?– Computer vision

Example: Image Acquisition

• Solar Eclipse: August 21st, 2017• Objective: Determine the progression of the

eclipse


• Image Acquisition device: IPhone 5 camera


• Image Acquisition device: Cardboard box with holes


• Nasa: Solar Dynamics Observatory

Source: https://www.nasa.gov/image-feature/goddard/2017/sdo-views-2017-solar-eclipse-171-angstrom

Example: Image Processing

Long-exposure photography: Involves using a long-duration shutter speed to sharply capture the stationary elements of images

Weeks 1 & 2 37

Origins of Digital Image Processing

Sent by submarine cable between London and New York, the transportation time was reduced to less than three hours from more than a week

38

Origins of Digital Image Processing

What are digital images?

Light

Example: Camera

Store as digital values

Image

CCD Sensor

Weeks 1 & 2 40

Electromagnetic (EM) energy spectrum

Light, an electromagnetic (EM) wave.

EM waves:1. Propagating sine wave of varying wavelengths2. Stream of massless particles travelling in a wave like pattern3. Each particle has a certain amount of energy (photon)

Grouped according to energy per photon

What are digital images?

EM radiationStore as digital values

Image

Appropriate Sensor

Types of Radiation• Images are as variable as the types of radiation that exist and

the ways in which radiation interacts with matter:

WHAT ARE DIGITAL IMAGES?• Images are as variable as the types of radiation that exist and

the ways in which radiation interacts with matter:

Weeks 1 & 2 46


Major usesGamma-ray imagingX-raysUltravioletVisible and infrared bandsMicrowave band:Radio band

Imaging in visible spectrum

• Camera

https://www.cyberphysics.co.uk/topics/light/camera.htm

Weeks 1 & 2 48

Examples: Automated Visual Inspection

The area in which the imaging system detected the plate

Results of automated reading of the plate content by the system

Weeks 1 & 2 49

Examples: Automated Visual Inspection

Weeks 1 & 2 50


Major usesGamma-ray imagingX-raysUltravioletVisible and infrared bands: light microscopy, astronomy, remote sensing, industry, and law enforcementMicrowave band:Radio band

Weeks 1 & 2 51


Major usesGamma-ray imagingX-raysUltravioletVisible and infrared bands: light microscopy, astronomy, remote sensing, industry, and law enforcementMicrowave band:Radio band

Nuclear Medicine

• Application of radioactive substances in the diagnosis and treatment of disease.

• Radio active substance is taken internally, intravenously, or orally.

• The emitted radiation is captured by a Gamma Camera

Weeks 1 & 2 53

Examples: Gama-Ray Imaging

Bone Scan

PET Scan

• Positron emission tomography

• Patient is given a radioactive isotope, it emits positron as it decays

• Positron meets electron, are annihilated and two gamma rays are given off.

https://en.wikipedia.org/wiki/Positron_emission_tomography

Weeks 1 & 2 55

Examples: Gama-Ray Imaging

PET Scan

Weeks 1 & 2 56


Major usesGamma-ray imaging: nuclear medicine and astronomical observationsX-raysUltravioletVisible and infrared bands: light microscopy, astronomy, remote sensing, industry, and law enforcementMicrowave band:Radio band

Weeks 1 & 2 57


Major usesGamma-ray imaging: nuclear medicine and astronomical observationsX-raysUltravioletVisible and infrared bands: light microscopy, astronomy, remote sensing, industry, and law enforcementMicrowave band:Radio band

X-Ray

• Oldest source of EM radiation used for imaging.• Cathode is heated, and it produces electrons• The electron strike the nucleus and X-rays are produced.• The human/object to be x-ray’d is placed between the

source and X-ray film.• The intensity is modified by absorption as they pass

through the patient.

https://www.orau.org/PTP/collection/xraytubescoolidge/coolidgeinformation.htm

Weeks 1 & 2 59

Examples: X-Ray Imaging

X-Ray

• Contrast enhanced radiography: Angiography• Obtain images of blood vessels (angiograms)• A catheter (small tube) is inserted into vein, and guided to a

blood vessel that needs to be studied. • An X-ray contrast medium is injected, before taking an X-ray.• This enhances the contrast of the blood vessel.

Weeks 1 & 2 61


X-Ray

• CAT Scan

https://en.wikipedia.org/wiki/CT_scan

Weeks 1 & 2 63


Weeks 1 & 2 64


Major usesGamma-ray imaging: nuclear medicine and astronomical observationsX-rays: medical diagnostics, industry, and astronomy, etc.UltravioletVisible and infrared bands: light microscopy, astronomy, remote sensing, industry, and law enforcementMicrowave band:Radio band

Weeks 1 & 2 65


Major usesGamma-ray imaging: nuclear medicine and astronomical observationsX-rays: medical diagnostics, industry, and astronomy, etc.Ultraviolet: lithography, industrial inspection, microscopy, lasers, biological imaging,and astronomical observationsVisible and infrared bands: light microscopy, astronomy, remote sensing, industry, and law enforcementMicrowave band: radarRadio band: medicine (such as MRI) and astronomy

GENERAL IMAGE TYPES• We can distinguish between three types of imaging, which create different

types of image information:• Reflection Imaging

– Image information is surface information; how an object reflects/absorbsincident radiation

• - Optical (visual, photographic, laser-based)• - Radar• - Sonar, ultrasound (non-EM)• - Electron microscopy

• Emission Imaging– Image information is internal information; how an object creates radiation

• - Thermal, infrared (FLIR) (geophysical, medical, military)• - Astronomy (stars, nebulae, etc.)• - Nuclear (particle emission, e.g., MRI)

• Absorption Imaging– Image information is internal information; how an object modifies/absorbs

radiation passing through it• - X-Rays in many applications• - Optical microscopy in laboratory applications• - Tomography (CAT, PET) in medicine• - “Vibro-Seis” in geophysical prospecting

SCALES OF IMAGING

• As varied as the scales found in nature

Weeks 1 & 2 68

Fundamental Steps in DIP

Result is more suitable than the original

Improving the appearance

Extracting image components

Partition an image into its constituent parts or objects

Represent image for computer processing

Digital Image Processing�COSC 6380/4393Digital Image Processing�COSC 6380/4393Introduction to the courseSlide Number 4Graduate Vs. UndergraduateLogisticsPlagiarismInterim grading policyTEXTBOOKRECOMMENDED BOOKS�Course ExpectationsClass WebsiteAccessing VideosAccessing VideosWatch VideosForum and DiscussionPost QuestionsPost QuestionAttending MeetingsMeetingMeetingAttend MeetingAttend MeetingPre-IntroductionPre-IntroductionPre-IntroductionPre-IntroductionWhy an Image?Why an Image?Image ProcessingImage ProcessingExample: Image AcquisitionExample: Image AcquisitionExample: Image AcquisitionExample: Image AcquisitionExample: Image ProcessingOrigins of Digital Image ProcessingOrigins of Digital Image ProcessingWhat are digital images?Electromagnetic (EM) energy spectrumWhat are digital images?Types of RadiationTypes of RadiationTypes of RadiationWHAT ARE DIGITAL IMAGES?Electromagnetic (EM) energy spectrumImaging in visible spectrum Examples: Automated Visual InspectionExamples: Automated Visual InspectionElectromagnetic (EM) energy spectrumElectromagnetic (EM) energy spectrumNuclear MedicineExamples: Gama-Ray Imaging PET ScanExamples: Gama-Ray Imaging Electromagnetic (EM) energy spectrumElectromagnetic (EM) energy spectrumX-Ray Examples: X-Ray Imaging X-Ray Examples: X-Ray Imaging X-Ray Examples: X-Ray Imaging Electromagnetic (EM) energy spectrumElectromagnetic (EM) energy spectrumGENERAL IMAGE TYPESSCALES OF IMAGINGFundamental Steps in DIP

digital image processingqil.uh.edu/dip/media/cosc6380/lecture_-_1_iojmhqx.pdf · 2021. 1. 21. ·...

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