Lecture Digital image processing: Spatial and frequency domain filter design - Nguyễn Công Phương

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Lecture Digital image processing - Spatial and frequency domain filter design include all of the following content: Spatial domain filter design (average/mean filter, median filter, gaussian smoothing, conservative smoothing), frequency – based filter design.

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Nội dung Text: Lecture Digital image processing: Spatial and frequency domain filter design - Nguyễn Công Phương

Nguyễn Công Phương DIGITAL IMAGE PROCESSING Spatial & Frequency Domain Filter Design
Contents I. Introduction to Image Processing & Matlab II. Image Acquisition, Types, & File I/O III. Image Arithmetic IV. Affine & Logical Operations, Distortions, & Noise in Images V. Image Transform VI. Spatial & Frequency Domain Filter Design VII. Image Restoration & Blind Deconvolution VIII. Image Compression IX. Edge Detection X. Binary Image Processing XI. Image Encryption & Watermarking XII. Image Classification & Segmentation XIII. Image – Based Object Tracking XIV. Face Recognition XV. Soft Computing in Image Processing sites.google.com/site/ncpdhbkhn 2
Spatial & Frequency Domain Filter Design 1. Spatial Domain Filter Design a) Average/Mean Filter b) Median Filter c) Gaussian Smoothing d) Conservative Smoothing 2. Frequency – Based Filter Design sites.google.com/site/ncpdhbkhn 3
Average/Mean Filter 100 105 104 1 110 150 101 9 102 103 104 sites.google.com/site/ncpdhbkhn 4
Median Filter • The median is calculated by first sorting all the elements in numerical order and then taking the middle one. • If the number of elements is even, the average of the two middle elements is used. sites.google.com/site/ncpdhbkhn 5
Spatial & Frequency Domain Filter Design 1. Spatial Domain Filter Design a) Average/Mean Filter b) Median Filter c) Gaussian Smoothing d) Conservative Smoothing 2. Frequency – Based Filter Design sites.google.com/site/ncpdhbkhn 6
Gaussian Smoothing ( m  m0 )2  ( n  n0 )2 1  h ( m, n )  e 2 2 2 2 sites.google.com/site/ncpdhbkhn 7
Conservative Smoothing • Conservative: not modifying the pixel blindly. • Algorithm: 1. A = min(neighborhood); 2. B = max(neighborhood); 3. Central pixel = • A, if cp < A, • B, if cp > B, • Else no change. sites.google.com/site/ncpdhbkhn 8
Spatial & Frequency Domain Filter Design 1. Spatial Domain Filter Design a) Average/Mean Filter b) Median Filter c) Gaussian Smoothing d) Conservative Smoothing 2. Frequency – Based Filter Design sites.google.com/site/ncpdhbkhn 9
Frequency – Based Filter Design FFT IFFT Image in Image in Image frequency Filter frequency Image domain domain sites.google.com/site/ncpdhbkhn 10