Denoising of Maritime Unmanned Aerial Vehicles Photography Based on Guidance Correlation Pixel Sampling and Aggregation

Abstract

In this paper, we proposed a guidance correlation pixel Sampling and aggregation image denoising for maritime Unmanned Aerial Vehicles(UAVs) photography, providing a reliable data base for maritime reconnaissance work. The overall step is mainly composed of two parts, pixel sampling and pixel aggregation. To improve the content correlation of sampled pixels, we propose a guided sampling scheme based on the basic estimated map and extend this algorithm to the restoration of maritime UAVs image. Finally, a UAVs image denoising system is shown. Our experimental results show that the proposed algorithm can effectively remove noise and achieves ${32.98}{dB}$ and ${31.83}{dB}$ in Set12 and BSD68 datasets with less and image distortion. In the actual scene, the PSNR of our denoising algorithm has reached ${35.33}{dB}$ , meets the basic needs of practical vision and follow-up research.

Keywords

• Image denoising
• guided sampling
• pixel aggregation network (PAN)
• UAVs photography