Digital Image Processing Frequency Filtering Ashourian

Slides:



Advertisements
Similar presentations
Image Enhancement in the Frequency Domain (2)
Advertisements

Image Enhancement in Frequency Domain Nana Ramadijanti Laboratorium Computer Vision Politeknik Elekltronika Negeri Surabaya PENS-ITS 2009.
Basic Properties of signal, Fourier Expansion and it’s Applications in Digital Image processing. Md. Al Mehedi Hasan Assistant Professor Dept. of Computer.
Frequency Domain Filtering (Chapter 4)
1 Image Processing Ch4: Filtering in frequency domain Prepared by: Tahani Khatib AOU.
Digital Image Processing
Image Enhancement in the Frequency Domain Part III
Image processing (spatial &frequency domain) Image processing (spatial &frequency domain) College of Science Computer Science Department
Digital Image Processing Lecture 11: Image Restoration Prof. Charlene Tsai.
© by Yu Hen Hu 1 ECE533 Digital Image Processing Image Enhancement in Frequency Domain.
Chap 4 Image Enhancement in the Frequency Domain.
Digital Image Processing, 2nd ed. © 2002 R. C. Gonzalez & R. E. Woods Chapter 5 Image Restoration Chapter 5 Image Restoration.
1 of 17 Digital Image Processing Image Enhancement Ashourian.
Digital Image Processing
Digtial Image Processing, Spring ECES 682 Digital Image Processing Oleh Tretiak ECE Department Drexel University.
Digital Image Processing: Revision
Reminder Fourier Basis: t  [0,1] nZnZ Fourier Series: Fourier Coefficient:
Chapter 4 Image Enhancement in the Frequency Domain.
CHAPTER 4 Image Enhancement in Frequency Domain
Image Enhancement in the Frequency Domain Part III Dr. Samir H. Abdul-Jauwad Electrical Engineering Department King Fahd University of Petroleum & Minerals.
Chap 4-2. Frequency domain processing Jen-Chang Liu, 2006.
General Functions A non-periodic function can be represented as a sum of sin’s and cos’s of (possibly) all frequencies: F(  ) is the spectrum of the function.
Digital Image Processing Chapter 4: Image Enhancement in the Frequency Domain.
Image Enhancement in the Frequency Domain Part II Dr. Samir H. Abdul-Jauwad Electrical Engineering Department King Fahd University of Petroleum & Minerals.
Chapter 4 Image Enhancement in the Frequency Domain.
Transforms: Basis to Basis Normal Basis Hadamard Basis Basis functions Method to find coefficients (“Transform”) Inverse Transform.
Digital Image Processing, 2nd ed. © 2002 R. C. Gonzalez & R. E. Woods Chapter 4 Image Enhancement in the Frequency Domain Chapter.
Filters in the Frequency Domain.  Image Smoothing Using Frequency Domain Filters: ◦ Ideal Lowpass Filters ◦ Butterworth Lowpass Filters ◦ Gaussian Lowpass.
Presentation Image Filters
Medical Image Analysis Image Enhancement Figures come from the textbook: Medical Image Analysis, by Atam P. Dhawan, IEEE Press, 2003.
Digital Image Processing Chapter # 4 Image Enhancement in Frequency Domain Digital Image Processing Chapter # 4 Image Enhancement in Frequency Domain.
Image Processing © 2002 R. C. Gonzalez & R. E. Woods Lecture 4 Image Enhancement in the Frequency Domain Lecture 4 Image Enhancement.
CS654: Digital Image Analysis
Digital Image Processing CSC331 Image Enhancement 1.
ENG4BF3 Medical Image Processing Image Enhancement in Frequency Domain.
Digital Image Processing Chapter 4: Image Enhancement in the Frequency Domain 22 June 2005 Digital Image Processing Chapter 4: Image Enhancement in the.
Digital Image Processing Lecture 11: Image Restoration March 30, 2005 Prof. Charlene Tsai.
Lecture Nine Figures from Gonzalez and Woods, Digital Image Processing, Copyright 2002.
Frequency Domain Processing Lecture: 3. In image processing, linear systems are at the heart of many filtering operations, and they provide the basis.
University of Ioannina - Department of Computer Science Filtering in the Frequency Domain (Application) Digital Image Processing Christophoros Nikou
Practical Image Processing1 Chap7 Image Transformation  Image and Transformed image Spatial  Transformed domain Transformation.
Low Pass Filter High Pass Filter Band pass Filter Blurring Sharpening Image Processing Image Filtering in the Frequency Domain.
بخش دوم.
Computer Graphics & Image Processing Chapter # 4 Image Enhancement in Frequency Domain 2/26/20161.
G52IIP, School of Computer Science, University of Nottingham 1 Image Transforms Basic idea Input Image, I(x,y) (spatial domain) Mathematical Transformation.
Digital Image Processing Lecture 9: Filtering in Frequency Domain Prof. Charlene Tsai.
Frequency Domain Filtering. Frequency Domain Methods Spatial Domain Frequency Domain.
Amity School of Engineering & Technology 1 Amity School of Engineering & Technology DIGITAL IMAGE PROCESSING & PATTERN RECOGNITION Credit Units: 4 Mukesh.
Digital Image Processing Lecture 8: Image Enhancement in Frequency Domain II Naveed Ejaz.
Digital Image Processing , 2008
Math 3360: Mathematical Imaging
Medical Image Analysis
IMAGE ENHANCEMENT IN THE FREQUENCY DOMAIN
IMAGE PROCESSING FREQUENCY DOMAIN PROCESSING
The content of lecture This lecture will cover: Fourier Transform
Spatial & Frequency Domain
Digital Image Processing
Gaussian Lowpass Filter
Image Enhancement in the
General Functions A non-periodic function can be represented as a sum of sin’s and cos’s of (possibly) all frequencies: F() is the spectrum of the function.
Digital Image Processing
Image Enhancement in the Frequency Domain Part I
Image Enhancement (Frequency Domain)
ENG4BF3 Medical Image Processing
Frequency Domain Analysis
4. Image Enhancement in Frequency Domain
Digital Image Processing
Lecture 4 Image Enhancement in Frequency Domain
Digital Image Processing Lecture 11: Image Restoration
Presentation transcript:

Digital Image Processing Frequency Filtering Ashourian

Contents بهبود کیفیت تصویر در حوزه فرکانس The Fourier series & the Fourier transform Image Processing in the frequency domain Image smoothing Image sharpening Fast Fourier Transform

DFT & Images قدرمطلق دامنه تبدیل فوریه DFT

DFT & Images

DFT & Images

Fourier spectrum of the image DFT & Images (cont…) DFT Scanning electron microscope image of an integrated circuit magnified ~2500 times Fourier spectrum of the image

DFT & Images (cont…)

DFT & Images (cont…)

The Inverse DFT تبدیل فوریه معکوس پذیر است for x = 0, 1, 2…M-1 and y = 0, 1, 2…N-1

The DFT and Image Processing برای فیلتر کردن در حوزه فرکانس: Compute F(u,v) the DFT of the image Multiply F(u,v) by a filter function H(u,v) Compute the inverse DFT of the result

Some Basic Frequency Domain Filters Low Pass Filter High Pass Filter

Some Basic Frequency Domain Filters

Some Basic Frequency Domain Filters

Smoothing Frequency Domain Filters هموارسازی با حذف بخش فرکانس بالای سیگنال صورت می گیرد The basic model for filtering is: G(u,v) = H(u,v)F(u,v) where F(u,v) is the Fourier transform of the image being filtered and H(u,v) is the filter transform function Low pass filters – only pass the low frequencies, drop the high ones

Ideal Low Pass Filter فیلتر پایین گذر ایده ال کلیه عواملی که کمتر از یک فرکانس ثابت هستند را حذف می نماید changing the distance changes the behaviour of the filter

Ideal Low Pass Filter (cont…) فیلتر پایین گذر ایده ال: where D(u,v) is given as:

Ideal Low Pass Filter (cont…) Above we show an image, it’s Fourier spectrum and a series of ideal low pass filters of radius 5, 15, 30, 80 and 230 superimposed on top of it

Ideal Low Pass Filter (cont…)

Ideal Low Pass Filter (cont…)

Ideal Low Pass Filter (cont…) Result of filtering with ideal low pass filter of radius 5 Original image Result of filtering with ideal low pass filter of radius 15 Result of filtering with ideal low pass filter of radius 30 Result of filtering with ideal low pass filter of radius 230 Result of filtering with ideal low pass filter of radius 80

Ideal Low Pass Filter (cont…) Result of filtering with ideal low pass filter of radius 5

Ideal Low Pass Filter (cont…) Result of filtering with ideal low pass filter of radius 15

Butterworth Lowpass Filters The transfer function of a Butterworth lowpass filter of order n with cutoff frequency at distance D0 from the origin is defined as: Images taken from Gonzalez & Woods, Digital Image Processing (2002)

Butterworth Lowpass Filter (cont…) Result of filtering with Butterworth filter of order 2 and cutoff radius 5 Original image Result of filtering with Butterworth filter of order 2 and cutoff radius 15 Result of filtering with Butterworth filter of order 2 and cutoff radius 30 Result of filtering with Butterworth filter of order 2 and cutoff radius 230 Result of filtering with Butterworth filter of order 2 and cutoff radius 80

Butterworth Lowpass Filter (cont…) Original image Result of filtering with Butterworth filter of order 2 and cutoff radius 5

Butterworth Lowpass Filter (cont…) Result of filtering with Butterworth filter of order 2 and cutoff radius 15

Gaussian Lowpass Filters The transfer function of a Gaussian lowpass filter is defined as:

Gaussian Lowpass Filters (cont…) Result of filtering with Gaussian filter with cutoff radius 5 Original image Result of filtering with Gaussian filter with cutoff radius 15 Result of filtering with Gaussian filter with cutoff radius 30 Result of filtering with Gaussian filter with cutoff radius 85 Result of filtering with Gaussian filter with cutoff radius 230

Lowpass Filters Compared Result of filtering with Butterworth filter of order 2 and cutoff radius 15 Result of filtering with ideal low pass filter of radius 15 Result of filtering with Gaussian filter with cutoff radius 15

Lowpass Filtering Examples فیلتر پایین گذر گوسین می تواند برای اتصال حروف شکسته استفاده شود

Lowpass Filtering Examples

Lowpass Filtering Examples (cont…) از فیلترهای پایین گذر گوسی مختلف می توان برای حذف چین و چروک یا روتوش استفاده نمود

Lowpass Filtering Examples (cont…)

Lowpass Filtering Examples (cont…) Original image Gaussian lowpass filter Spectrum of original image Processed image

Sharpening in the Frequency Domain لبه ها و جزییات تصویر متناظر با عوامل فرکانس بالا هستند High pass filters – only pass the high frequencies, drop the low ones High pass frequencies are precisely the reverse of low pass filters, so: Hhp(u, v) = 1 – Hlp(u, v)

Ideal High Pass Filters :فیلتر بالاگذر ایده ال بدین صورت داده می شود where D0 is the cut off distance as before

Ideal High Pass Filters (cont…) Results of ideal high pass filtering with D0 = 15 Results of ideal high pass filtering with D0 = 30 Results of ideal high pass filtering with D0 = 80

Butterworth High Pass Filters The Butterworth high pass filter is given as: where n is the order and D0 is the cut off distance as before

Butterworth High Pass Filters (cont…) Results of Butterworth high pass filtering of order 2 with D0 = 15 Results of Butterworth high pass filtering of order 2 with D0 = 80 Results of Butterworth high pass filtering of order 2 with D0 = 30

Gaussian High Pass Filters فیلتر بالا گذر گوسی بدین صورت تعریف میشود: where D0 is the cut off distance as before

Gaussian High Pass Filters (cont…) Results of Gaussian high pass filtering with D0 = 15 Results of Gaussian high pass filtering with D0 = 80 Results of Gaussian high pass filtering with D0 = 30

Highpass Filter Comparison Results of ideal high pass filtering with D0 = 15

Highpass Filter Comparison Results of Butterworth high pass filtering of order 2 with D0 = 15

Highpass Filter Comparison Results of Gaussian high pass filtering with D0 = 15

Highpass Filter Comparison Results of ideal high pass filtering with D0 = 15 Results of Butterworth high pass filtering of order 2 with D0 = 15 Results of Gaussian high pass filtering with D0 = 15

Highpass Filter Comparison Results of ideal high pass filtering with D0 = 15

Highpass Filter Comparison Results of Butterworth high pass filtering of order 2 with D0 = 15

Highpass Filter Comparison Results of Gaussian high pass filtering with D0 = 15

Highpass Filtering Example Original image Highpass filtering result High frequency emphasis result After histogram equalisation

Highpass Filtering Example

Highpass Filtering Example

Highpass Filtering Example

Highpass Filtering Example

Laplacian In The Frequency Domain 2-D image of Laplacian in the frequency domain Laplacian in the frequency domain Inverse DFT of Laplacian in the frequency domain Zoomed section of the image on the left compared to spatial filter

Frequency Domain Laplacian Example Laplacian filtered image Original image Laplacian image scaled Enhanced image

Fast Fourier Transform The reason that Fourier based techniques have become so popular is the development of the Fast Fourier Transform (FFT) algorithm Allows the Fourier transform to be carried out in a reasonable amount of time Reduces the amount of time required to perform a Fourier transform by a factor of 100 – 600 times!

Frequency Domain Filtering & Spatial Domain Filtering Similar jobs can be done in the spatial and frequency domains Filtering in the spatial domain can be easier to understand Filtering in the frequency domain can be much faster – especially for large images

Summary we examined image enhancement in the frequency domain The Fourier series & the Fourier transform Image Processing in the frequency domain Image smoothing Image sharpening Fast Fourier Transform Next time we will begin to examine image restoration using the spatial and frequency based techniques.

Imteresting Application Of Frequency Domain Filtering

Imteresting Application Of Frequency Domain Filtering

Questions? ?