The aim of this chapter is to review: (1) the Sampling (Nyquist) Theorem; (2) the concept of aliasing; (3) the importance of antialiasing low-pass filtering for eliminating the effect of aliasing and appropriately determining the sampling frequency; (4) the advantages of properly chosen ...
The aliasing phenomenon is not confined to MRI but is present in all types of technology, explaining audible distortions of sound, moire patterns in photos, and unnatural motion in cinema. The "wagon wheel effect" is a familiar example of aliasing. In this optical illusion, spokes on a wheel...
highly visible in repetitive patterns such as fabrics. Demosaicing programs (programs that fill in the missing colors in the raw image) use sophisticated algorithms to infer missing detail in each color from detail in the other colors. These algorithms can have a significant effect on color moiré...
So far, we've explored thetheoretical underpinnings of the Nyquist-Shannon theorem, including thefrequency domain effect on sampling. We then touched on how these foundational principles apply in real-life circuit design—specifically, addressing the importance ofoversampling in real-life mix...
itscutofffrequencyissetathalfthesamplingratefs,thefrequencybandofthe signal after the filter is graphically shown in Fig. 6.1. Shanghai Institute of Technology School of Mechanical Engineering Figure 6.1. Ideal anti-aliasing filter effect. The light grey area represents the signal ...
2011on that topic and its usage in Crysis 2 [1]. Crytek proposed using a sub pixel jitter to the final MVP transformation matrix that alternates every frame – and combine two frames in post-effect style pass. This way they were able to increase the sampling resolution twice at almost no...
Section 3 introduces the SS-AWSTFT algorithm to construct high-resolution SAFE distribution and the skew calibration model considering the rotational effect for parameter identification. In Sections 4 Numerical validations, 5 Experimental validation, simulations and experiments are carried out to respectively...
Aliasing is an effect that causes distortion in the spectrum of a sampled signal due to the sampling rate being too low to capture the frequency content properly. Aliasing causes high frequency data to appear at a lower frequency than it actually is (see Figure 1 below): thus assuming a “...
The ability to quiet the analog front-end sampling is one example. The charging/discharging at the inputs as the converter transitions back to acquisition has always been a difficult problem. The typical knock on effect was that much higher speed driver amplifiers were required. With ...
In this work, we illustrate why similar caution is needed when resampling images under general spa- tial transformations and propose a novel method that is more respectful of the sampling theorem, minimising aliasing and loss of information. We introduce the notion of scale factor point spread ...