The I3A Camera Phone Image Quality (CPIQ) visual noise metric described is a core image quality attribute of the wider
I3A CPIQ consumer orientated, camera image quality score. This paper describes the selection of a suitable noise metric,
the adaptation of the chosen ISO 15739 visual noise protocol for the challenges posed by cell phone cameras and the
mapping of the adapted protocol to subjective image quality loss using a published noise study. Via a simple study,
visual noise metrics are shown to discriminate between different noise frequency shapes. The optical non-uniformities
prevalent in cell phone cameras and higher noise levels pose significant challenges to the ISO 15739 visual noise
protocol. The non-uniformities are addressed using a frequency based high pass filter. Secondly, the data clipping at high
noise levels is avoided using a Johnson and Fairchild frequency based Luminance contrast sensitivity function (CSF).
The final result is a visually based noise metric calibrated in Quality Loss Just Noticeable Differences (JND) using
Aptina Imaging's subjectively calibrated image set.