Objective Assessment of Perceptual Audio Quality Using ViSQOLAudio

Digital audio broadcasting services transmit substantial amounts of data that is encoded to minimize bandwidth whilst maximizing user quality of experience. Many large service providers continually alter codecs to improve the encoding process. Performing subjective tests to validate each codec alteration would be impractical, necessitating the use of objective perceptual audio quality models. This paper evaluates the quality scores from ViSQOLAudio, an objective perceptual audio quality model, against the quality scores of PEAQ, POLQA, and PEMO-Q on three datasets containing fullband audio encoded with a variety of codecs and bitrates. The results show that ViSQOLAudio was more accurate than all other models on two of the datasets and performed well on the third, demonstrating the utility of ViSQOLAudio for predicting the perceptual audio quality for encoded music

Automated colour grading using colour distribution transfer

This article proposes an original method for grading the colours between different images or shots. The first stage of the method is to find a one-to-one colour mapping that transfers the palette of an example target picture to the original picture. This is performed using an original and parameter free algorithm that is able to transform any N-dimensional probability density function into another one. The proposed algorithm is iterative, non-linear and has a low computational cost. Applying the colour mapping on the original picture allows reproducing the same ‘feel’ as the target picture, but can also increase the graininess of the original picture, especially if the colour dynamic of the two pictures is very different. The second stage of the method is to reduce this grain artefact through an efficient post-processing algorithm that intends to preserve the gradient field of the original picture