The mean squared error (MSE) and its related metrics such as peak signal to noise ratio (PSNR), root mean squared error (RMSE) and signal to noise ratio (SNR) have been the basis for mathematically defined image quality measurement for a long time. These methods are all based on the MSE. Denoised image quality has also been traditionally measured in terms of the MSE or its derivatives. However, none of these metrics takes the structural fidelity of the image into account. We investigate the structural changes that occur during the denoising process and attempt to study an alternative metric for determining the quality of denoised images based on structural changes. We also show the shortcomings of the MSE-based image quality metrics.
|Number of pages||12|
|Journal||International Journal of Circuits, Systems and Signal Processing|
|Publication status||Published - 2011 Oct 17|
ASJC Scopus subject areas
- Signal Processing
- Electrical and Electronic Engineering