Video Compression With CNN-Based Postprocessing

Image Compression by Cnn

Track-Based Video Compression

An alternative to conventional techniques for compressing video data of moving objects is described. The method, known as track-based compression (TBC), detects, associates, and tracks moving objects between frames, sending only a small chip or ID around the moving object once the track has been established. The compression ratio achievable depends on scene content, sensor geometry, the degree ...

Segmentation-Based Postprocessing in Real-Time Immersive Video Conferencing

We present a novel, real-time disparity analysis frame work developed for immersive teleconferencing. This two-stage method computes a limited number of highly reliable disparities in the first step and then, filling the remaining holes based on segmentation information. The disparity algorithm is a hybrid recursive matching (HRM) approach. Its computational effort is minimised by the efficient...

Postprocessing for Three-dimensional Discrete Cosine Transform Based Video Coding

A three-dimensional DCT (3D-DCT) block-based video compression (3D-DCT VC) could be a promising solution for limited memory, processing power and energy consumption computation platforms. Providing reduced computation complexity and being free from error-drift problem, it, however, suffers from a “blockiness” of decoded video due to the coarse quantization of transform coefficients, in the same...

Object - based Postprocessing of Block Motion FieldsFor Video

It is likely that in many applications block-matching techniques for motion estimation will be further used. In this paper, a novel object-based approach for enhancement of motion elds generated by block matching is proposed. Herein, a block matching is rst applied in parallel with a fast spatial image segmentation. Then, a rule-based object postprocessing strategy is used where each object is ...