This directory contains a few OpenEXR files with unusual numbers
in their pixels.  The files can be used to test how application
programs behave when they encounter pixels with very small, very
large or non-finite pixel values:


WideColorGamut.exr

    Some pixels in this RGB image have extremely saturated colors,
    outside the gamut that can be displayed on a video monitor whose
    primaries match Rec. ITU-R BT.709.  All RGB triples in the image
    correspond to CIE xyY triples with xy chromaticities that represent
    real colors.  (In a chromaticity diagram, the pixels are all inside
    the spectral locus.)  However, for pixels whose chromaticities are
    outside the triangle defined by the chromaticities of the Rec. 709
    primaries, at least one of the RGB values is negative.


AllHalfValues.exr

    The pixels in this RGB HALF image contain all 65,536 possible
    16-bit floating-point numbers, including positive and negative
    numbers, normalized and denormalized numbers, zero, NaNs,
    positive infinity and negative infinity.


WideFloatRange.exr

    This image contains only a single G channel of type FLOAT.
    The values in the pixels span almost the entire range of
    possible 32-bit floating-point numbers (roughly -1e38 to +1e38).


BrightRings.exr

    This RGB image contains a number of rather bright rings, with
    pixel values over 1000, on a gray background.  The image is useful
    for testing how filtering and resampling algorithms react to high-
    dynamic-range data.  (Some filters, for example, convolution kernels
    with negative lobes, tend to produce objectionable artifacts near
    high-contrast edges.)
    Note that the rings in the image are smooth, although on most displays
    clamping of the pixel values introduces aliasing artifacts.  To see
    that the rings really are smooth, view the image with exrdisplay and
    set the exposure to -10.


BrightRingsNanInf.exr

    This image is the same as BrightRings.exr, except for a few
    pixels near the center, which contain NaNs and infitities.


SquaresSwirls.exr

    This image contains colored squares and swirling patterns against a
    flat gray background.  Applying lossy compression algorithms to this
    image tends to highlight compression artifacts.

