Downsampling
Downsampling - Related Videos
01:20
Downsampling
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2024
When considering a sampled sequence with zero values between sampling instants, one can replace it by taking every N-th value of the sequence. At these integer multiples of N, the original and sampled sequences coincide. This process, known as decimation, involves extracting every N-th sample from a sequence, thereby creating a more efficient sequence. The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...
10:59
Reconstruction of 3-Dimensional Histology Volume and its Application to Study Mouse Mammary Glands
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Cited by 10 •
2014
We present an image registration approach for 3-dimensional (3D) histology volume reconstruction, which facilitates the study of the changes of an organ at the level of macrostructures made up of cells . Using this approach, we studied the 3D changes between wild-type and Igfbp7-null mammary glands.
FAQs
The low-pass filter removes or attenuates frequency content that should not remain after the sampling-rate reduction. If those components are left in the signal, the reduced sample spacing can make them overlap with other frequency components. This aliasing cannot be reversed reliably afterward, so filtering before decimation protects the information band that the system intends to retain.
The integer factor determines how many output samples remain and therefore how much storage, transmission, and processing can be reduced. However, a larger reduction leaves less allowable signal bandwidth after filtering. Engineers must select a factor that matches the receiving component's data rate while retaining the frequency content needed for the intended task.
Proper downsampling controls the signal bandwidth before samples are removed, whereas simple deletion can leave frequency components that become overlapped after the rate reduction. The distinction is important because discarded samples cannot be recovered, and aliasing permanently changes the represented signal. Filtering and a suitable integer factor therefore make the reduction more controlled and useful.
First, determine the desired output rate or integer reduction factor. Next, apply a low-pass filter that limits the signal bandwidth appropriately. Finally, retain samples according to the selected decimation factor and verify that the resulting data rate suits the next system component. This sequence reduces data while protecting essential signal information from aliasing.
Engineers should consider the signal bandwidth that must be preserved, the target data rate, and the acceptable balance between information retention and resource savings. The filter must limit content that could overlap after reduction, while the integer factor must be compatible with the system architecture. These choices determine whether storage, transmission, and processing benefits occur without losing essential information.
Applications include audio and image processing, sensor systems, communications, and digital control. In each case, reducing the data rate can lower storage needs, transmission requirements, or computational load. The technique also helps match data rates between system components, allowing a downstream stage to receive a more manageable stream while preserving the signal content relevant to its operation.