Alan C. Bovik

TL;DR: A new distortion-specific no-reference video quality model for predicting banding artifacts, called the Blind BANding Detector (BBAND index), which is inspired by human visual models.

TL;DR: A rate-adaptation algorithm is proposed that can incorporate QoE constraints on the empirical cumulative quality distribution per user and can reduce network resource consumption over conventional average-quality maximized rate- Adaptation algorithms.

TL;DR: This paper proposes an open framework for image retargeting quality assessment, where the quality prediction engine is a trained Radial Basis Function (RBF) neural network and the network is trained on ten perceptually relevant features, including a saliency-weighted, SIFT-directed complex wavelet structural similarity (CW-SSIM) index, and a new image aesthetics evaluation method.

TL;DR: The experimental results show that, even with no prior knowledge, the new VQA algorithm performs better than the full reference (FR) quality measure PSNR, which makes it a very good candidate for real time signal processing applications.

TL;DR: This study finds that a onesided generalized gaussian distribution closely fits the prior of the range gradient, which sheds new light on statistical modeling of 2D and 3D image features in natural scenes.