Rate-Constrained Region of Interest Coding Using Adaptive Quantization in Transform Domain Wyner–Ziv Video Coding

In this paper, we propose a rate-constrained distributed video coding-based region of interest (ROI) coding scheme. The proposed scheme appropriately determines ROI according to an available bit budget that depends on transmission channel and decoding environment. Its subjective quality is faithfully maintained via adaptive ROI definition of the available resources. Prior knowledge about the ROI is represented in terms of Gaussian mixture weighting function, which in turn determines the ROI according to the number of available bits. An adaptive quantization method is used in the ROI bit allocation. Compared to the existing non-ROI-based schemes, the proposed scheme not only improves the ROI coding performance but also the subjective quality of the entire picture.