vista.algorithms.background_removal.temporal_median.TemporalMedian¶

class vista.algorithms.background_removal.temporal_median.TemporalMedian(imagery, name='Temporal Median', background=5, offset=2)[source]¶

Temporal median background removal algorithm.

Removes background by computing the median of surrounding frames, excluding a temporal offset around the current frame. This approach is effective for detecting moving objects against a relatively static background.

Parameters:

imagery (Imagery) – The multi-frame imagery dataset to process.
name (str, optional) – Name identifier for this algorithm instance. Default is “Temporal Median”.
background (int, optional) – Number of frames on each side (left and right) to use for computing the median background. Default is 5.
offset (int, optional) – Number of frames to skip on each side of the current frame before including frames in the background calculation. This prevents the current frame and immediately adjacent frames from influencing the background estimate. Default is 2.

_current_frame¶

Internal counter tracking the current frame being processed. Initialized to -1 and incremented on each call.

Type:: int

Notes

The algorithm computes a background estimate using frames in two windows: - Left window: [current - offset - background : current - offset] - Right window: [current + offset + 1 : current + offset + background + 1]

The median of all frames in these windows is subtracted from the current frame to produce the foreground image.

Examples

>>> from vista.imagery import Imagery
>>> imagery = Imagery.from_file('data.h5')
>>> temporal_median = TemporalMedian(imagery, background=5, offset=2)
>>> frame_idx, foreground = temporal_median()

__init__(imagery, name='Temporal Median', background=5, offset=2)¶

Methods

__init__(imagery[, name, background, offset])

Attributes

`background`
`name`
`offset`
`imagery`

imagery: Imagery¶

name: str = 'Temporal Median'¶

background: int = 5¶

offset: int = 2¶

__call__()[source]¶

Process the next frame and return the background-removed result.

Returns:

frame_idx (int) – Index of the processed frame.
foreground (NDArray) – The background-removed frame, computed as current_frame - median_background. Has the same shape as the input imagery frames.

Return type:

Tuple[int, ndarray[tuple[Any, …], dtype[_ScalarT]]]

Notes

This method maintains internal state (_current_frame) and should be called sequentially for each frame. Calling it multiple times will process successive frames in order.

__init__(imagery, name='Temporal Median', background=5, offset=2)¶