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Sampling is the process of making the x-axis (time) discrete and quantization is the process of making the y-axis (magnitude) discrete. You can sample without quantization (such as done with an analog sample and hold circuit). Quantization is introduced through rounding or truncation when the sampled analog signal is mapped to a digital representation.
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Can we consider these noises as salt and pepper noise.? Is there something else that I am missing?
several pixels getting erased to either zero or one -> yeah, that fits my definition of salt and pepper noise. However, there might be other definitions around, including assumptions of noise autocorrelation, and whether or not your noise fulfills these is ...
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The second image you find online as you mentioned is magnitude and the first image must be either real part or the imaginary part (but not both). If you calculate complex value magnitude for each point, i.e. $Mag_{i,j} = R_{i,j}^2 + I_{i,j}^2$ you get something similar to the following image.
I = imread('cameraman.tif');
F = fft2(I);
F_Centered = fftshift(F)...
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The digital image acquisition sensor (CMOS, CCD etc) is typically defined with a physical area of H x W (usually expressed in diagonal length in mm) and number of photo-sensitive elements; the pixels. PPI is not a part of sensor specifications for cameras, (but it can be for scanners yet you're dealing with smart phone cameras).
The Nyquist rate of an image ...
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Here are a few tools you might find helpful for annotating and generating Ground Truth segmentation masks:
Xyonix Vannot - Video Annotation Tool for Object Segmentation
Best image annotation platforms for computer vision (+ an honest review of each)
Playment.io's Video Annotation tool
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Many people, including Andrew Ng in his Deep Learning Specialization, emphasize the importance of domain knowledge and developing hand crafted features. Only then one can achieve significant improvements in performance. A. Ng clearly talks about how hand crafted features are nowadays looked down upon but in fact, are important. Fundamental concepts in signal/...
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