A resource-efficient parallel architecture for infrared image stripe noise removal based on the most stable window

Stripe noise is a common phenomenon arises in the multi-detectors infrared imaging equipment, which not only generally destroys the quality of the image, but also seriously affects the subsequent processing of the image. We exploit the stripe noise features of infrared image, and find that the adjacent noise difference can be well described by the difference of the mean values of adjacent rows in infrared images with the mean compensation and the two-point correction principle. Based on this, a novel stripe noise removal algorithm based on stable window is designed, it is not only effective to remove stripe noise in infrared image without causing undesired blurring effects and artifacts, but also efficient in terms of storage and computing resource utilization for real-time processing. In addition, in order to meet the demands of image real-time processing on satellites, we also design a low-latency, low-energy and highly-paralleled architecture for the de-noising algorithm, and implement it on a field programmable gate array (FPGA) processor. Experimental results show that the proposed algorithm outperforms the other current methods, and it can not only has a better performance in visual effect and objective quality than other state-of-the-art de-noising methods, but also has obvious advantages in the consumption of storage resources due to the design of resource-efficient parallel architecture. For instance, in the consumption of Block RAM storage, compared with the TPC method, this proposed algorithm reduces 80% memory, and gets a significant improvement of the processing speed.