Motion Estimation-Assisted Denoising for an Efficient Combination with an HEVC Encoder.

Abstract

Noise, which is commonly generated in low-light environments or by low-performance cameras, is a major cause of the degradation of compression efficiency. In previous studies that attempted to combine a denoise algorithm and a video encoder, denoising was used independently of the code for pre-processing or post-processing. However, this process must be tightly coupled with encoding because noise affects the compression efficiency greatly. In addition, this represents a major opportunity to reduce the computational complexity, because the encoding process and a denoise algorithm have many similarities. In this paper, a simple, add-on denoising scheme is proposed through a combination of high-efficiency video coding (HEVC) and block matching three-dimensional collaborative filtering (BM3D) algorithms. It is known that BM3D has excellent denoise performance but that it is limited in its use due to its high computational complexity. This paper employs motion estimation in HEVC to replace the block matching of BM3D so that most of the time-consuming functions are shared. To overcome the challenging algorithmic differences, the hierarchical structure in HEVC is uniquely utilized. As a result, the computational complexity is drastically reduced while the competitive performance capabilities in terms of coding efficiency and denoising quality are maintained.