Compressive Sensed Video Coding Having Jpeg Compatibility - Belyaev, Evgeny (Proceedings - International Conference on Image Processing, 2020)
This paper studies the problem of video coding based on compressive sensing (CS) framework. We propose a new approach based on global sensing model applied to a residual frame computed as a difference between an input frame and its downsampled and upsampled version. The downsampled version of the frame is compressed via JPEG baseline making the codec compatible with JPEG. The sensed measurements are quantized, subsampled using a predefined look-up table, and encoded via context-adaptive binary range coder. The resulting bit stream is divided into network abstract layer packets which are embedded into an application part of the JPEG header. Experimental results show that the proposed approach outperforms existing algorithms based on CS in rate-distortion performance and generates a bit stream, which is significantly more robust to packet losses compared to conventional codecs.