The term, objective measurements refer to the description of the physical characteristics within the digital radiographic system. They have the ability to describe the performance of the whole imaging system by referring to the image quality. These physical measures include a signal to noise ratio (SNR), contrast to noise ratio (CNR), a modulation transfer function (MTF), a noise power spectrum (NPS) and a detective quantum efficiency (DQE) (Månsson, 2000, & Seeram, Bushong, Davidson, & Swan, 2014). This sub-section will consider the most commonly adopted measures, namely DQE, CNR and specifically the SNR.
SNR measurement explains the relationship between contrast and noise levels in an image for an object with a large scale. In this context, SNR is a simplistic method commonly used to describe the visibility of an object in the image (Lança & Silva, 2008). It can be determined by a ratio of mean signal value in the studied object (i.e. the mean signal difference between object and its background) to the standard deviation of the signal value of the background (Båth, 2010). SNR is widely used to assess the image quality of digital radiographic images. This is because, in digital radiography, the main determinant factor of image quality is the noise level. SNR’s relationship to human observer detectability was first studied by Albert Rose in 1948 (Rose, 1973). He attempted to discover the minimal noise level required for an image to be viewed by the human eye. He found that a ratio value of ≥5 is required as a threshold for detectability. As such, SNR calculation provides a figure for image quality measurements based on connecting the mathematically calculated SNR to the findings of detection examinations