Subpixel Shifting
Subpixel Shifting - Related Videos
09:12
Sound Waves and Doppler Shift
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2023
Source: Arianna Brown, Asantha Cooray, PhD, Department of Physics & Astronomy, School of Physical Sciences, University of California, Irvine, CA Waves are disturbances that propagate through a material medium or empty space. Light waves can travel through a vacuum and some forms of matter, and are transverse in nature, which means that the oscillations are perpendicular to the direction of propagation. However, sound waves are pressure waves that travel through an elastic medium like air,...
06:57
Electrophoretic Mobility Shift Assay (EMSA)
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2023
The electrophoretic mobility shift assay (EMSA) is a biochemical procedure used to elucidate binding between proteins and nucleic acids. In this assay a radiolabeled nucleic acid and test protein are mixed. Binding is determined via gel electrophoresis which separates components based on mass, charge, and conformation. This video shows the concepts of EMSA and a general procedure, including gel and protein preparation, binding, electrophoresis, and detection. Applications covered in this video...
09:45
New Variations for Strategy Set-shifting in the Rat
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Cited by 3 •
2017
Set-shifting, a form of behavioral flexibility, requires an attentional shift from one stimulus dimension to another. We extended an established rodent set-shifting task1 by requiring attention to different stimuli according to context. The task was combined with specific lesions to identify neuron subtypes underlying a successful shift.
01:21
Shifts in PPF
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2024
Note that 'rotation' can be considered a specific type of 'shift' where the PPF changes its slope due to alterations in the relative efficiency of producing different goods The concept of a shift in the Production Possibility Frontier (PPF) illustrates changes in an economy's maximum output potential for two goods or services. A shift occurs when there is a change in factors such as technology, resources, or the labor force, leading to alterations in production capabilities. For instance,...
01:28
Shift of the IS Curve I
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2026
The IS curve shows the combinations of interest rates and output where total spending in the goods market is equal to total production. The position of the curve changes when the government changes its spending or taxation policies. These changes affect how much households and businesses spend in the economy.When government spending increases, overall demand rises. For example, if the government spends money on improving water supply systems, construction companies and workers receive payments...
FAQs
Each controlled shift places the same biological feature at a different position relative to the detector’s pixels. These positions provide complementary intensity measurements rather than repeatedly sampling the feature in exactly the same way. Computational integration of those measurements increases effective spatial sampling, helping reconstruct finer detail from the collected low-resolution images.
Registration aligns the multiple images so that corresponding biological features contribute to the same reconstructed locations. Acquisition stability helps preserve the intended relationships among the shifted views. If alignment is inaccurate or the imaging process is unstable, complementary intensity information may not combine correctly, reducing the reliability of the higher-resolution reconstruction and subsequent measurements.
The approach improves effective spatial sampling through multiple shifted acquisitions and computational reconstruction rather than by requiring changes to the optical system or illumination wavelength. This distinction makes it relevant when an existing imaging platform must be extended without altering those components. Its benefit therefore comes from coordinated image acquisition and processing.
The detector pixel grid determines where each feature is sampled in every acquired image. Slight shifts change that sampling relationship, so different images contain distinct intensity information about the same structure. The reconstruction algorithm uses these differences to assemble a more finely sampled representation, which can support clearer visualization and more detailed image-based analysis.
A typical workflow begins by capturing multiple low-resolution images with slight, controlled shifts. The images are then registered to account for their relative positions, and a computational algorithm integrates their complementary intensity information. The resulting reconstruction can be examined for finer structural detail and used for quantitative measurements, provided acquisition stability and registration accuracy are maintained.
Bioengineers can apply the technique to microscopy of cells, tissues, and biomaterials when they need improved visualization of small structures without changing the existing optical system or illumination wavelength. The reconstructed images may support quantitative image-based measurements and extend the capabilities of established imaging platforms, making the method relevant across several biological and engineered material contexts.