Binary image

A binary image assigns one of two values to every pixel, commonly $0$ and $1$ or false and true. It can represent a selected region, such as marks separated from a page background, without retaining all the original brightness values. The two values express a chosen classification of pixels, not necessarily two physical colors in the original scene.

For example, define image thresholding by selecting intensities at least $100$:The output preserves which side of the threshold each value occupied but loses the distinction between $120$ and $150$. Changing the threshold changes the selected region, so interpreting the result requires the selection rule as well as the image.

A binary image is useful as input to connected-component labeling. There, pixel connectivity determines whether diagonally touching selected pixels belong to the same region. SciPy's labeling operation accepts zero as background and all nonzero values as foreground; an input with several nonzero intensities is consequently treated as a foreground mask by that particular API.^[ref]

Two possibilities require one bit of information per pixel in a direct packed representation. An actual array or image file can use more storage, or compression can exploit repeated patterns. Also distinguish a binary image from a label image containing several region identifiers: a label value of three need not mean brighter foreground than a label value of one.