Non-Local Mean Denoising of Multi-Layer With Adaptive Filtering Strength Based on ASIC Implementation

Image denoising is an important algorithm in ASIC real-time image processing. Research has found that after cascaded spatial and temporal denoising, video images still exhibit patches and structural noise. To reduce the noise of this type while considering factors such as hardware resource overhead in ASIC implementation, this paper proposes a multi-layer adaptive threshold denoising method based on Non-Local Mean algorithm and pyramid framework. This algorithm performs spatial noise removal on Y channel image data in the YUV domain. Y component is firstly gaussian downsampled into 2 additional layers which is 1/4 and 1/2 scale of the original. Secondly, adaptive filtering strengths are estimated using DCT to further improve the NLM performance within each layer; Finally, the denoised results from the three-layer filtering are fused and output. Through comparison, the proposal can significantly suppress structural noise such as plagues. Meanwhile, our ASIC implementation of MRNLM can achieve real-time video denoising on-the-fly without outer memory access and the on-chip ASIC is kept minimal.