Psycho-visual quality assessment of state-of-the-art denoising schemes

In this paper we compare the quality of 7 state-of-the-art denoising schemes based on human visual perception. 3 of those are wavelet-based filter schemes, 1 is Discrete Cosine Transform-based, 1 is Discrete Fourier Transform-based, 2 are Steerable Pyramid-based and 1 is Fuzzy Logic based. A psycho-visual experiment was set up in which 37 subjects were asked to score and compare denoised images coming from 3 different scenes. A Multi-Dimensional Scaling framework was then used to process the data of this experiment. This lead to a ranking of the filters in perceived overall image quality. In a follow-up experiment other attributes such as the noisiness, bluriness and artefacts present in the denoised images allowed us also to determine why people choose one filter over the other.