The phrase peak signal-to-noise ratio, often abbreviated PSNR, is an engineering term for the ratio between the maximum value of a signal and the magnitude of background noise. Because many signals have a very wide dynamic range, PSNRs are usually expressed in terms of the logarithmicdecibel scale.
The PSNR is most commonly used as a measure of quality of reconstruction in image compression etc. It is most easily defined via the mean squared error which for two mxn images I and K is defined as:
The PSNR is defined as:
Here, MAXI is the maximum pixel value of the image. In most cases this is 255. The logarithm is base 10.
For color images with three RGB values per pixel the definition of PSNR is the same. Only the MSE is the sum over all squared value differences divided by image size and by three.
Typical values for the PSNR in image compression are between 20 and 40 dB.
На практике видео изображение со значениями PSNR порядка 40-43 dB и выше является изображением высокого качества, в то время как значения порядка 30 dB и ниже характеризуют изображение плохого качества.
Значение PSNR, вычисляемое программой, включает оценку всех промежуточных этапов кодирования, рассмотренных выше: преобразование RGB-24 в YUV, пространственное изменение разрешения цветности (UV) в драйвере, кодирование YUV-компонент, обратную процедуру передискретизации цветности и обратное преобразование YUV в RGB-24.
The phrase peak signal-to-noise ratio, often abbreviated PSNR, is an engineering term for the ratio between the maximum possible power of a signal and the power of corrupting noise that affects the fidelity of its representation.
The PSNR is most commonly used as a measure of quality of reconstruction in image compression etc. It is most easily defined via the mean squared error (MSE) which for two m×n monochrome images I and K where one of the images is considered a noisy approximation of the other is defined as:
For color images with three RGB values per pixel, the definition of PSNR is the same except the MSE is the sum over all squared value differences divided by image size and by three.
Feeds |
Contact