Cube-based Video Coding Framework for Block-based Compressive Imaging

Block-based compressive imaging enables new video acquisition methodology while reducing raw data size, theoretically eliminating the need for complex coding algorithms. However, the redundancy associated with random projection remains when transmitting raw data. This paper takes a fresh look at raw data structure by viewing it as cube made up of multiple downsampled images rather than a vector. As a result, each individual data point can be regarded as a pixel, allowing us to code with greater flexibility and versatility than current works. Following that, we propose a tailored video coding framework for this structure that includes directional 9 modes intra and inter prediction with block-matching motion estimation, transformation using DCT, and quantization with custom 4×4 quantization table as shown in Figure 1. We evaluated coding performance using various 4K datasets, resulting in 60-65% lower bit-per-pixels while maintaining visual quality compared to state-of-the-art works [1].