Xu Jizheng

TL;DR: An image dehazing model built with a convolutional neural network (CNN) based on a re-formulated atmospheric scattering model, called All-in-One Dehazing Network (AOD-Net), which demonstrates superior performance than the state-of-the-art in terms of PSNR, SSIM and the subjective visual quality.

TL;DR: This paper analyzes the ME structure in HEVC and proposes a parallel framework to decouple ME for different partitions on many-core processors and achieves more than 30 and 40 times speedup for 1920 × 1080 and 2560 × 1600 video sequences, respectively.

TL;DR: This paper proposes a parallel framework to decide coding unit trees through in-depth understanding of the dependency among different coding units, and achieves averagely more than 11 and 16 times speedup for 1920x1080 and 2560x1600 video sequences, respectively, without any coding efficiency degradation.

TL;DR: An overview of the technical features and characteristics of the current HEVC-SCC test model and related coding tools, including intra-block copy, palette mode, adaptive color transform, and adaptive motion vector resolution are provided.

TL;DR: In this article, a three-dimensional embedded subband coding with optimized truncation (3-D ESCOT) algorithm is proposed, in which coefficients in different subbands are independently coded using fractional bit-plane coding and candidate truncation points are formed at the end of each fractional bits-plane.