Lecture Digital image processing: Affine & logical operations, distortions, & noise in images - Nguyễn Công Phương

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Lecture Digital image processing: Affine & logical operations, distortions, & noise in images include the following content: Affine operations, logical operators, noise in images, distortions in images.

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Nội dung Text: Lecture Digital image processing: Affine & logical operations, distortions, & noise in images - Nguyễn Công Phương

Nguyễn Công Phương DIGITAL IMAGE PROCESSING Affine and Logical Operations, Distortions, and Noise in Images
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
Image Arithmetic 1. Affine Operations a) Translation b) Rotation c) Scaling 2. Logical Operators 3. Noise in Images 4. Distortions in Images sites.google.com/site/ncpdhbkhn 3
Affine Operations • An affine operation/transformation maps variables into new variables by applying a linear combination of translation, rotation, and scaling (TRS) operations  x2   x1  y   Ay  B  2  1 sites.google.com/site/ncpdhbkhn 4
Translation  x2  1 0  x1   b1   y   0 1  y   b   2    1  2  • Pixel movement by b1 in x & b2 in y direction. • Used to improve visualization of an image. sites.google.com/site/ncpdhbkhn 5
Rotation  x2  cos   sin    x1   x0   y    sin       cos    y1   y0   2  • Rotates all pixels by an angle of θ degrees (counterclockwise for positive angle) • Used to improve the visual appearance of an image. sites.google.com/site/ncpdhbkhn 6
Scaling  x2   a11 0   x1  0  y    0 a   y   0  2  22   1    • Performs a geometric transformation that can be used to shrink or zoom the size of an image. • Image reduction/subsampling: replacement (of a group of pixel values by one arbitrarily chosen pixel, a11 or a22, value from within this group), or by interpolating between pixel values. • Image zooming: achieved by pixel replication or by interpolation sites.google.com/site/ncpdhbkhn 7
Image Arithmetic 1. Affine Operations 2. Logical Operators a) AND & NAND b) OR & NOR c) XOR & XNOR d) NOT 3. Noise in Images 4. Distortions in Images sites.google.com/site/ncpdhbkhn 8
AND & NAND • Used to: – Compute the intersection of two images, – Extract a portion of an image. A B AND NAND 0 0 0 1 0 1 0 1 AND  AB 1 0 0 1 NAND  ( AB ) 1 1 1 0 Binary operator Grayscale operator sites.google.com/site/ncpdhbkhn 9
OR & NOR A B OR NOR 0 0 0 1 0 1 1 0 OR  A  B 1 0 1 0 NOR  ( A  B ) 1 1 1 0 Binary operator Grayscale operator sites.google.com/site/ncpdhbkhn 10
Image Arithmetic 1. Affine Operations 2. Logical Operators a) AND & NAND b) OR & NOR c) XOR & XNOR d) NOT 3. Noise in Images 4. Distortions in Images sites.google.com/site/ncpdhbkhn 11
XOR & XNOR A B XOR XNOR 0 0 0 1 0 1 1 0 XOR  AB  AB 1 0 1 0 XNOR  ( AB  AB ) 1 1 0 1 Binary operator Grayscale operator sites.google.com/site/ncpdhbkhn 12
NOT A A’ 0 1 A  2b  1  A 1 0 Binary operator Grayscale operator sites.google.com/site/ncpdhbkhn 13
Image Arithmetic 1. Affine Operations 2. Logical Operators 3. Noise in Images 4. Distortions in Images sites.google.com/site/ncpdhbkhn 14
Noises in Images • Photon noise: due to the stochastic nature of photon generation. • Thermal noise: electrons are released due to thermal activity & get trapped in the CCD wells. • On – chip electronic noise: originates in the process of reading the signal from the sensor. • KTC noise: associated with the gate capacitor of an FET. • Amplifier noise: in modern well – designed electronics, it is generally negligible. • Quantization noise: occurs in the analog – to – digital converter (ADC). sites.google.com/site/ncpdhbkhn 15
Distortions in Images • Commonly called blur. • Linear motion blur: due to relative motion between the recording device and the object. • Uniform out – of – focus blur: when a camera on a 2D imaging plane images a 3D object, some parts of the object are in focus whereas other parts are not. • Atmospheric turbulence blur: due to a long – term exposure case. • Scatter blur: the incident imaging quanta are reflected by the system structure or other incident quanta. sites.google.com/site/ncpdhbkhn 16