Search results
Results from the WOW.Com Content Network
Peak signal-to-noise ratio (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. Because many signals have a very wide dynamic range, PSNR is usually expressed as a logarithmic quantity using the decibel scale.
Signal to noise ratio may be abbreviated as SNR and less commonly as S/N. PSNR stands for peak signal-to-noise ratio. GSNR stands for geometric signal-to-noise ratio. [13] SINR is the signal-to-interference-plus-noise ratio.
PSNR (Peak Signal-to-Noise Ratio) Image: It is calculated between every frame of the original and the degraded video signal. PSNR is the most widely used objective image quality metric. However, PSNR values do not correlate well with perceived picture quality due to the complex, highly non-linear behaviour of the human visual system.
Typical signal quality measures involving noise are signal-to-noise ratio (SNR or S/N), signal-to-quantization noise ratio (SQNR) in analog-to-digital conversion and compression, peak signal-to-noise ratio (PSNR) in image and video coding and noise figure in cascaded amplifiers.
Due to its popularity, SSIM is often compared to other metrics, including more simple metrics such as MSE and PSNR, and other perceptual image and video quality metrics. SSIM has been repeatedly shown to significantly outperform MSE and its derivates in accuracy, including research by its own authors and others.
Based on peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM) metrics and known ground-truth images for testing performance, it is concluded that iterative directional total variation has a better reconstructed performance than the non-iterative methods in preserving edge and texture areas. The orientation field refinement ...
The quality of a compression method often is measured by the peak signal-to-noise ratio. It measures the amount of noise introduced through a lossy compression of the image, however, the subjective judgment of the viewer also is regarded as an important measure, perhaps, being the most important measure.
Traditionally, SNR is defined to be the ratio of the average signal value to the standard deviation of the signal : [2] [3] = when the signal is an optical intensity, or as the square of this value if the signal and noise are viewed as amplitudes (field quantities).